User’s Manual for RESRAD-BUILD Version 3 · ANL/EAD/03-1 User’s Manual for RESRAD-BUILD Version 3 Environmental Assessment Division Argonne National Laboratory Operated by The

ANL/EAD/03-1

User’s Manual for RESRAD-BUILD Version 3

Environmental Assessment Division

Argonne National Laboratory

Operated by The University of Chicago,under Contract W-31-109-Eng-38, for the

United States Department of Energy

DISCLAIMERThis report was prepared as an account of work sponsored by an agency ofthe United States Government. Neither the United States Government norany agency thereof, nor The University of Chicago, nor any of theiremployees or officers, makes any warranty, express or implied, or assumesany legal liability or responsibility for the accuracy, completeness, orusefulness of any information, apparatus, product, or process disclosed, orrepresents that its use would not infringe privately owned rights. Referenceherein to any specific commercial product, process, or service by trade name,trademark, manufacturer, or otherwise does not necessarily constitute orimply its endorsement, recommendation, or favoring by the United StatesGovernment or any agency thereof. The views and opinions of documentauthors expressed herein do not necessarily state or reflect those of theUnited States Government or any agency thereof, Argonne NationalLaboratory, or The University of Chicago.

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Available for a processing fee to U.S. Department ofEnergy and its contractors, in paper, from:

U.S. Department of EnergyOffice of Scientific and Technical InformationP.O. Box 62Oak Ridge, TN 37831-0062phone: (865) 576-8401fax: (865) 576-5728email: [email protected]

ANL/EAD/03-1

User’s Manual for RESRAD-BUILD Version 3

by C. Yu, D.J. LePoire, J.-J. Cheng, E. Gnanapragasam, S. Kamboj,J. Arnish, B.M. Biwer, A.J. Zielen, W.A. Williams,* A. Wallo III,* and H.T. Peterson, Jr.*

Environmental Assessment DivisionArgonne National Laboratory, 9700 South Cass Avenue, Argonne, Illinois 60439

June 2003

Work sponsored by U.S. Department of Energy, Assistant Secretary for Environment,Safety, and Health, Office of Environmental Policy and Assistance, and Assistant Secretaryfor Environmental Management, Office of Site Closure

______________________

* Wallo and Peterson are affiliated with the Office of Environmental Policy and Assistance and Williamswith the Office of Site Closure, U.S. Department of Energy, Washington, D.C.

NOTICE

This formal technical report is an information product of Argonne’sEnvironmental Assessment Division (EAD). It presents results ofcompleted studies that are broader in scope than those reported intechnical memoranda issued by EAD. This report has been internallyreviewed and edited and has been externally peer reviewed byindividuals who are not associated with Argonne or the sponsoringagency.

For more information on the division’s scientific and engineeringactivities, contact:

Director, Environmental Assessment DivisionArgonne National LaboratoryArgonne, Illinois 60439Telephone (630) 252-3107email: [email protected]

Publishing support services were provided by Argonne’s Information andPublishing Division.

This report is printed on recycled paper.

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CONTENTS

PREFACE ............................................................................................................................ xi

ACKNOWLEDGMENTS.................................................................................................... xiii

DOE FOREWORD .............................................................................................................. xv

NOTATION ......................................................................................................................... xvii

ABSTRACT......................................................................................................................... 1-1

1 INTRODUCTION.......................................................................................................... 1-3

2 DESCRIPTIONS OF BUILDINGS, SOURCES, AND RECEPTORS......................... 2-1

2.1 Building Description ............................................................................................. 2-12.2 Source Descriptions............................................................................................... 2-32.3 Receptor Descriptions ........................................................................................... 2-5

3 DESCRIPTIONS OF EXPOSURE SCENARIOS AND PATHWAYS........................ 3-1

3.1 Exposure Scenarios ............................................................................................... 3-13.2 Exposure Pathways ............................................................................................... 3-23.3 Input Data Templates ............................................................................................ 3-2

4 USER’S GUIDE............................................................................................................. 4-1

4.1 Installation............................................................................................................. 4-14.2 Navigation and File Management ......................................................................... 4-24.3 Input Windows ...................................................................................................... 4-4

4.3.1 Case Window ............................................................................................ 4-44.3.2 Building Parameters .................................................................................. 4-5

4.3.2.1 Room Details for One-Room Model.......................................... 4-54.3.2.2 Room Details for Two-Room Model ......................................... 4-54.3.2.3 Room Details for Three-Room Model ....................................... 4-5

4.3.3 Receptor Parameters.................................................................................. 4-84.3.4 Shielding Parameters................................................................................. 4-94.3.5 Source Parameters ..................................................................................... 4-94.3.6 Radiological Units..................................................................................... 4-13

4.4 Results Windows................................................................................................... 4-164.4.1 Text Output ............................................................................................... 4-164.4.2 Graphic Output.......................................................................................... 4-18

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CONTENTS (Cont.)

4.5 Procedures for Using Probabilistic Analysis......................................................... 4-204.5.1 Input Window............................................................................................ 4-21

4.5.1.1 Sample Specifications ................................................................ 4-214.5.1.2 Parameter Distributions.............................................................. 4-224.5.1.3 Input Rank Correlations ............................................................. 4-234.5.1.4 Output Specifications ................................................................. 4-24

4.5.2 Output Results ........................................................................................... 4-254.5.2.1 Interactive Output....................................................................... 4-264.5.2.2 Interactive Graphical Output...................................................... 4-284.5.2.3 Complete Tabular Report ........................................................... 4-294.5.2.4 Complete Formatted Results File............................................... 4-32

5 VERIFICATION OF THE RESRAD-BUILD COMPUTER CODE............................ 5-1

5.1 Verification Procedure .......................................................................................... 5-15.2 Results and Discussion.......................................................................................... 5-2

6 REFERENCES............................................................................................................... 6-1

APPENDIX A: Indoor Air Quality Model.......................................................................... A-1

APPENDIX B: Air Particulate Deposition ......................................................................... B-1

APPENDIX C: Radon and Its Progeny Concentration ....................................................... C-1

APPENDIX D: Inhalation of Airborne Radioactive Dust .................................................. D-1

APPENDIX E: Ingestion of Radioactive Material.............................................................. E-1

APPENDIX F: External Radiation Exposure...................................................................... F-1

APPENDIX G: Exposures to Tritium in Buildings ............................................................ G-1

APPENDIX H: Calculation of Integrated Doses ................................................................ H-1

APPENDIX I: Uncertainty Analysis................................................................................... I-1

APPENDIX J: Parameter Descriptions ............................................................................... J-1

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TABLES

3.1 Key Parameters Used in the Building Occupancy and BuildingRenovation Scenarios............................................................................................... 3-4

5.1 Comparison of RESRAD-BUILD and Spreadsheet Pathway Dosesfor Different Source Types....................................................................................... 5-3

5.2 Comparison of RESRAD-BUILD and MCNP Dose Values for the DirectExternal Exposure Pathway ..................................................................................... 5-3

C.1 Values of Rate Constants Used in the Radon Progeny Model................................. C-15

D.1 Committed Effective Dose Equivalent Conversion Factors for Inhalation.............. D-6

E.1 Committed Effective Dose Equivalent Conversion Factors for InternalRadiation from Ingestion.......................................................................................... E-6

F.1 Fitted Parameters Ai, Bi, KAi, and KBi Used to Calculate Depthand Cover Factors for 67 Radionuclides ................................................................. F-6

F.2 Effective Dose Equivalent Conversion Factors for External GammaRadiation from Contaminated Ground .................................................................... F-11

I.1 Statistical Distributions Used in RESRAD-BUILD and TheirDefining Parameters................................................................................................. I-8

J.1 Cumulative Distribution Function for the Indoor Fraction........................................ J-8

J.2 Relative Frequency of Hours Worked by Persons Working 35 Hoursor More per Week...................................................................................................... J-8

J.3 Statistics for Fraction of Time Spent Indoors at Work.............................................. J-9

J.4 Statistics for Fraction of Time Spent Indoors in a Residence.................................... J-11

J.5 Estimated Indoor Deposition Velocities by Particle Size.......................................... J-22

J.6 Estimated Deposition Velocities by Particle Size in Residenceswith and without Furniture ........................................................................................ J-24

J.7 Estimated Indoor Deposition Velocities for Various Radionuclides......................... J-24

J.8 Indoor Resuspension Rates........................................................................................ J-31

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TABLES (Cont.)

J.9 Resuspension Factors from Previous Studies ............................................................ J-33

J.10 Room Height in New Conventional and Manufactured Homes, 1996...................... J-37

J.11 Residential Air Exchange Rate Distribution Characteristics..................................... J-44

J.12 Outside Air Exchange Rates for Commercial Buildings ........................................... J-46

J.13 Inhalation Rate Distributions..................................................................................... J-63

J.14 Summary of EPA’s Recommended Values for Inhalation ........................................ J-64

J.15 Indirect Ingestion Rates ............................................................................................. J-67

J.16 Influence of Surface and Contaminant Types on Smear Tests.................................. J-83

J.17 Percent Removal of Contamination for Different Sampling Methods ...................... J-84

J.18 Source Lifetime Variation with Air Exchange Rate and RoomHeight for a Fixed Resuspension Factor of 1 × 10-6 m-1............................................ J-88

J.19 Source Lifetime and Resuspension Factor for Different RemovableFractions for a House with an Air Exchange Rate of 0.5 h-1 and a2.3-m Room Height ................................................................................................... J-89

J.20 Density of Source Materials Allowed in RESRAD-BUILD ..................................... J-98

J.21 Source Density from Various Sources....................................................................... J-99

J.22 Bulk Density and Porosity of Rocks Commonly Used as Building Materials .......... J-106

J.23 Density of Shielding Materials Allowed in RESRAD-BUILD................................. J-122

J.24 Shielding Density from Various Sources................................................................... J-122

FIGURES

2.1 Vertical View of Possible Building Geometries for theRESRAD-BUILD Code............................................................................................. 2-2

2.2 Example of a Coordinate System Used in the RESRAD-BUILD Code.................... 2-3

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FIGURES (Cont.)

3.1 Exposure Pathways Incorporated into the RESRAD-BUILD Code.......................... 3-3

4.1 Main Menu................................................................................................................. 4-3

4.2 Case Window............................................................................................................. 4-4

4.3 Evaluation Times Window ........................................................................................ 4-6

4.4 Building Parameters Window.................................................................................... 4-6

4.5 Room Details for One-Room Model ......................................................................... 4-6

4.6 Room Details for Two-Room Model......................................................................... 4-7

4.7 Room Details for Three-Room Model....................................................................... 4-7

4.8 Receptor Parameters Window ................................................................................... 4-8

4.9 Shielding Parameters Window .................................................................................. 4-9

4.10 Source-Receptor Table Window................................................................................ 4-10

4.11 Copy Shielding Window............................................................................................ 4-10

4.12 Source Parameters Window....................................................................................... 4-11

4.13 Volume Source Detail Window................................................................................. 4-11

4.14 Area Source Detail Window...................................................................................... 4-12

4.15 Line Source Detail Window ...................................................................................... 4-12

4.16 Point Source Detail Window ..................................................................................... 4-13

4.17 Nontritium Volume Source Wall Regions Window.................................................. 4-14

4.18 Tritium Volume Source Parameters Window............................................................ 4-14

4.19 Interactive 3-D Display Window............................................................................... 4-15

4.20 Radiological Units Window ...................................................................................... 4-15

4.21 Window Displayed during Calculations .................................................................... 4-16

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FIGURES (Cont.)

4.22 Output Report ............................................................................................................ 4-17

4.23 RESRAD-BUILD Graphics Wizard Window........................................................... 4-19

4.24 Stacked Chart Showing the Dose to Each Receptor for Each Pathwayfor Source 1................................................................................................................ 4-19

4.25 Bar Chart of Dose to Receptor 3 for Each Radionuclideand Pathway Combination......................................................................................... 4-20

4.26 Sample Specifications Tab Screen............................................................................. 4-21

4.27 Parameter Distributions Tab Screen .......................................................................... 4-23

4.28 Input Rank Correlation Tab Screen ........................................................................... 4-24

4.29 Output Specifications Tab Screen.............................................................................. 4-25

4.30 Window Displayed When Calculations Are Being Performed ................................. 4-26

4.31 Input Specifications Tab Screen ................................................................................ 4-27

4.32 Parameter Distributions Tab Screen .......................................................................... 4-27

4.33 Text Results Tab Screen ............................................................................................ 4-28

4.34 Graphics Results Tab Screen ..................................................................................... 4-29

4.35 Probabilistic Output Report File................................................................................ 4-31

A.1 Schematic Representation of the Three-Compartment Building,Showing the Inflow and Outflow of Air in Each Compartment ............................... A-4

B.1 Schematic Representation of a Compartment i of the Building,Showing the Deposition of Dust Particulates onto the ProjectedHorizontal Surface ..................................................................................................... B-4

C.1 Three-Dimensional Schematic Representation of a Volume Source......................... C-5

C.2 One-Dimensional Schematic Representation of a Volume Source ........................... C-5

C.3 Schematic Representation of the Three-Compartment Building............................... C-11

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FIGURES (Cont.)

C.4 Schematic Representation of the Interrelationships among the SeveralStates of the Short-Lived Radon Decay Products...................................................... C-13

F.1 Geometry in the Line Source Model.......................................................................... F-9

G.1 Schematic Representation of the Dry Zone and Wet Zone Consideredin the Tritium Transport Model ................................................................................. G-7

J.1 Indoor Fraction Cumulative Distribution Function foran Occupational Setting............................................................................................ J-10

J.2 Examples of Potential Discrete Airflow Regimes in a Building .............................. J-17

J.3 Idealized Representation of Indoor Particle Deposition Velocity ............................ J-21

J.4 Trimodal Nature of Aerosol Particle Size Distribution ............................................ J-21

J.5 Indoor Deposition Velocity Probability Distribution ............................................... J-25

J.6 Indoor Resuspension Rate Probability Density Function ......................................... J-35

J.7 Room Height Probability Density Function ............................................................. J-37

J.8 Probability Density Function for Room Area........................................................... J-39

J.9 Building Air Exchange Rate Probability Density Function ..................................... J-46

J.10 Inhalation Rate Probability Density Function .......................................................... J-65

J.11 Indirect Ingestion Rate Probability Density Function .............................................. J-68

J.12 Source Direction for Line, Area, and Volume Sources ............................................ J-75

J.13 Air Release Fraction Probability Density Function.................................................. J-79

J.14 Removable Fraction Probability Distribution........................................................... J-83

J.15 Time for Source Removal or Source Lifetime Probability Density Function .......... J-88

J.16 Source Thickness Probability Density Function....................................................... J-96

J.17 Concrete Source Density Probability Distribution Function .................................... J-100

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FIGURES (Cont.)

J.18 Source Erosion Rate Probability Density Function .................................................. J-103

J.19 Concrete Source Porosity Probability Density Function .......................................... J-106

J.20 Radon Effective Diffusion Coefficient ..................................................................... J-109

J.21 Radon Emanation Fraction ....................................................................................... J-112

J.22 Shielding Thickness Probability Density Function .................................................. J-120

J.23 Concrete Shielding Density Probability Density Function....................................... J-123

J.24 Wet + Dry Zone Thickness Probability Density Function ....................................... J-129

J.25 Water Fraction Available for Evaporation Probability Density Function ................ J-133

J.26 Default Indoor Absolute Humidity Probability Density Function ........................... J-135

J.27 Representative Probability Density Function for Outdoor Ambient Humidity........ J-136

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PREFACE

In 1994, a manual was released on using the RESRAD-BUILD code to analyze theradiological doses resulting from human activities at buildings contaminated with radioactivematerial. Since then, the manual and code have been used widely by the U.S. Department ofEnergy and its contractors, the U.S. Nuclear Regulatory Commission, and many othergovernment agencies and institutions. New features, some in response to comments receivedfrom users, have been incorporated into the code to form RESRAD-BUILD Version 3. Theseimprovements have increased RESRAD-BUILD’s capabilities and flexibility and enabled usersto interact with the code more easily. RESRAD-BUILD Version 3 represents the third majorversion of the code since it was first released in 1994.

The RESRAD-BUILD code can now perform uncertainty/probabilistic analysis with animproved probabilistic interface.1 It uses a preprocessor and a postprocessor to performprobabilistic dose analysis.2 It incorporates default parameter distributions (based on nationalaverage data) for the selected parameters. The code can provide analysis results as text reports,interactive output, and graphic output. The results of an uncertainty analysis can be used as abasis for determining the cost-effectiveness of obtaining additional information or data on inputparameters (variables).3

The RESRAD-BUILD code now allows users to calculate the time-integrated dose overthe exposure duration at user-specified times. The instantaneous dose over the exposure durationcan be calculated by setting the time integration point to one. The other major changes in thecode are the new external exposure model for volume and area sources and a new tritium modelfor volume sources. In addition, the RESRAD-BUILD database has been updated. It nowincludes inhalation and ingestion dose conversion factors from U.S. Environmental ProtectionAgency Federal Guidance Report No. 11 (FGR-11),4 direct external exposure and air submersion

1 Yu, C., et al., 2000, Development of Probabilistic RESRAD 6.0 and RESRAD-BUILD 3.0 Computer Codes,

ANL/EAD/TM-98, NUREG/CR-6697, prepared by Argonne National Laboratory, Argonne, Ill., forU.S. Nuclear Regulatory Commission, Washington, D.C., Dec.

2 LePoire, D., et al., 2000, Probabilistic Modules for the RESRAD and RESRAD-BUILD Computer Codes, UserGuide, ANL/EAD/TM-91, NUREG/CR-6692, prepared by Argonne National Laboratory, Argonne, Ill., forU.S. Nuclear Regulatory Commission, Washington, D.C., Nov.

3 Kamboj, S., et al., 2000, Probabilistic Dose Analysis Using Parameter Distribution Developed for RESRAD andRESRAD-BUILD Codes, ANL/EAD/TM-89, NUREG/CR-6676, prepared by Argonne National Laboratory,Argonne, Ill., for U.S. Nuclear Regulatory Commission, Washington, D.C., July.

4 Eckerman, K.F., et al., 1988, Limiting Values of Radionuclide Intake and Air Concentration and DoseConversion Factors for Inhalation, Submersion, and Ingestion, EPA-520/1-88-020, Federal Guidance ReportNo. 11, prepared by Oak Ridge National Laboratory, Oak Ridge, Tenn., for U.S. Environmental ProtectionAgency, Office of Radiation Programs, Washington, D.C.

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dose conversion factors from FGR-12,5 and radionuclide half-lives from InternationalCommission on Radiological Protection Publication 38.6

RESRAD-BUILD Version 3 incorporates many improvements made since the code wasfirst released in 1994. A table for easier input and review of source/receptor shielding propertieshas been added. The code now has an improved 3-D display to illustrate source-receptorlocations. Users can now input radionuclide activity in SI units, and the resultant dose can alsobe reported in SI units. The help file in the code and the table of contents of the text report havebeen improved and are now much easier to use and navigate. This latest version of theRESRAD-BUILD code can be run only on computers with Windows operating systems(Windows 95, 98, NT, XP, and 2000). The DOS version of RESRAD-BUILD is no longersupported. Furthermore, to take advantage of the latest computer technology, the RESRAD-BUILD FORTRAN programs are now being compiled with the FORTRAN 95(LAHEY/FUJITSU LF95) compiler. Also, the Windows interface, which was initially developedin 16-bit Visual Basic 4.0, has been upgraded to 32-bit Visual Basic 6.0.

The RESRAD-BUILD code is part of the RESRAD family of codes, which now has itsown Web site (http://www.ead.anl.gov/resrad). The site has information on updates to the codes,and users can download the most recent release of the code of interest. The site also containsinformation on upcoming training workshops and links to many documents relevant toapplication of the particular code. Users can get technical assistance via e-mail ([email protected]).User’s manuals for several of the RESRAD family of codes, including RESRAD-BUILDVersion 3, can also be found on the RESRAD Web site in Adobe pdf format. A CD-ROMcontaining the RESRAD family of codes and supporting documents is available upon request.

This manual is a user’s guide for operating RESRAD-BUILD Version 3 and a referencemanual on the algorithms and formulas used in RESRAD-BUILD. Because this version reflects anumber of changes in the RESRAD-BUILD code, it is very different from previous versions.Many parts were added (e.g., Section 5 on verification and Appendixes G, H, I, and J on thetritium model for volume sources, calculating time-integrated doses, uncertainty analysis, andparameter descriptions). Other parts were extensively modified (e.g., the Section 4 user’s guideand Appendix F on external radiation exposure). The Section 3 discussion on exposure scenarioswas expanded to include default data template files for building occupancy and buildingrenovation scenarios.

The RESRAD-BUILD code is continuously being updated and improved. Some plannedimprovements include risk calculations, graphic output, and addition of radionuclides. Theseimprovements are not included in this manual. Users are encouraged to visit the RESRAD Website for the most recent improvements to the code. 5 Eckerman, K.F., and J.C. Ryman, 1993, External Exposure to Radionuclides in Air, Water, and Soil, Exposure to

Dose Coefficients for General Application, based on the 1987 Federal Radiation Protection Guidance, EPA 402-R-93-081, Federal Guidance Report No. 12, prepared by Oak Ridge National Laboratory, Oak Ridge, Tenn., forU.S. Environmental Protection Agency, Office of Radiation and Indoor Air, Washington, D.C.

6 International Commission on Radiological Protection, 1993, Radionuclide Transformations: Energy andIntensity Emissions, ICRP Publication 38, Annals of the ICRP, Vols. 11–13, Pergamon Press, New York, N.Y.

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ACKNOWLEDGMENTS

The RESRAD-BUILD code and the user’s manual were first published in November1994. Since then, the code has undergone various modifications and enhancements, resulting inthe release of Version 3. Although Version 3 includes new, improved models, many of themodels used in previous releases have been retained.

Numerous individuals who contributed to the previous versions of the code and manualhave not been listed as coauthors of the current manual. The authors would like to thank thefollowing individuals for their past contributions and continued interest in the development andimprovement of RESRAD-BUILD: Celso Loureiro, Lynn Jones, Inseok Baek, and Tim Klett.The authors would like to thank Tony Dvorak, Director of Argonne National Laboratory’sEnvironmental Assessment Division, and Shih-Yew Chen, Strategic Area Manager of Risk andWaste Management for the Division, for their continued support. The authors would like to thankDon Mackenzie and the late John Russell, who made important and useful contributions toRESRAD-BUILD development. The authors would also like to thank Tin Mo and his colleaguesat the U.S. Nuclear Regulatory Commission for their support for the improvement of theprobabilistic modules.

Editorial and document preparation services were provided by staff members ofArgonne’s Information and Publishing Division.

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xv

DOE FOREWORD

RESRAD-BUILD is a computer code designed to evaluate the radiation doses fromRESidual RADioactivity in BUILDings. This version of RESRAD-BUILD is the third majorrevision of the code. The RESRAD-BUILD code was developed by Argonne NationalLaboratory under sponsorship of the U.S. Department of Energy (DOE) and other federalagencies.

The first version of RESRAD-BUILD was released in 1994 for a DOS computerplatform. The second version was released in 1996 and used a Windows platform. Version 3 hasbeen prepared with extensive improvements in both the computational and user modules. Thisversion of RESRAD-BUILD supercedes the previous versions, and the sponsors believe it willbe useful in demonstrating compliance with the radiation protection requirements of DOE andother federal and state agencies.

The RESRAD activities at Argonne National Laboratory are sponsored by the DOEOffice of Environmental Policy and Assistance and the DOE Office of EnvironmentalManagement. Other federal agencies have made noteworthy contributions; in particular,substantial improvements in the uncertainty modules were made under the sponsorship of theU.S. Nuclear Regulatory Commission, with Dr. Tin Mo as the project manager.

RESRAD-BUILD may be used to demonstrate compliance with dose-baseddecommissioning requirements for structures and for evaluating radiation exposures withinstructures. Because of the intended regulatory use, the source code for RESRAD-BUILD is notprovided without written direction by DOE. Persons wishing to obtain the source code (forscientific review, possible modification, or translation into other languages) should request thesource code from the DOE sponsors with a written justification. The justification should specifyin detail the intended work, the modifications under consideration, the use of the code output,and the use of any new code segments. This degree of control over the source code is considerednecessary by DOE to control the configuration of RESRAD-BUILD and to ensure compliancewith regulatory requirements.

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xvii

NOTATION

The following is a list of the acronyms, initialisms, and abbreviations (including units ofmeasure) used in this document.

ACRONYMS, INITIALISMS, AND ABBREVIATIONS

AMAD activity median aerodynamic diameterANS American Nuclear SocietyAP anterior-posteriorARF airborne release fractionASHRAE American Society of Heating, Refrigeration, and Air-Conditioning EngineersASTM American Society for Testing and MaterialsBLS Bureau of Labor StatisticsBNL Brookhaven National LaboratoryCDF cumulative distribution functionCEDE committed effective dose equivalentCG correlated/uncorrelated groupingDCF dose conversion factorDOE U.S. Department of EnergyEF error factorEPA U.S. Environmental Protection AgencyFGR Federal Guidance ReportGI gastrointestinalG-P geometric progressionHT tritium gasHTO tritiated water (tritium oxide)HVAC heating, ventilation, and air-conditioningIAEA International Atomic Energy AgencyICRP International Commission on Radiological ProtectionISO International Organization for StandardizationLHS Latin hypercube samplingMCNP Monte Carlo N-particleNAHB National Association of Home BuildersNBS National Bureau of StandardsNCDC National Climatic Data CenterNRC U.S. Nuclear Regulatory CommissionPA posterior-anteriorPCC partial correlation coefficientpdf probability density functionPFT perfluorocarbon tracerpmf probability mass functionPRCC partial rank correlation coefficientRAM random access memory

xviii

Rf resuspension factorRF respirable fractionRG random groupingRH relative humiditySF6 sulfur hexafluorideSRC standardized partial regression coefficientSRRC standardized partial rank regression coefficientSRS simple random samplingTEDE total effective dose equivalent3-D three-dimensional

UNITS OF MEASURE

atm atmosphere(s)Bq becquerel(s)°C degree(s) Celsiuscm centimeter(s)cm2 square centimeter(s)cm3 cubic centimeter(s)Ci curie(s)d day(s)°F degree(s) Fahrenheitft foot (feet)ft2 square foot (feet)g gram(s)h hour(s)in. inch(es)K kelvin(s)kg kilogram(s)

m meter(s)m2 square meter(s)m3 cubic meter(s)MB megabyte(s)MeV megaelectron volt(s)mg milligram(s)min minute(s)mol mole(s)mrem millirem(s)MW molecular weightpCi picocurie(s)s second(s)WL working level(s)WLM working level month(s)yr year(s)µg microgram(s)µm micrometer(s)

1-1

USER’S MANUAL FOR RESRAD-BUILD VERSION 3

by

C. Yu, D.J. LePoire, J.-J. Cheng, E. Gnanapragasam, S. Kamboj, J. Arnish,B.M. Biwer, A.J. Zielen, W.A. Williams, A. Wallo III, and H.T. Peterson, Jr.

ABSTRACT

The RESRAD-BUILD computer code is a pathway analysis modeldesigned to evaluate the potential radiological dose incurred by an individual whoworks or lives in a building contaminated with radioactive material. The transportof radioactive material within the building from one compartment to another iscalculated with an indoor air quality model. The air quality model considers thetransport of radioactive dust particulates and radon progeny due to air exchange,deposition and resuspension, and radioactive decay and ingrowth. A single run ofthe RESRAD-BUILD code can model a building with up to three compartments,four source geometries (point, line, area, and volume), 10 distinct sourcelocations, and 10 receptor locations. The volume source can be composed of up tofive layers of different materials, with each layer being homogeneous andisotropic. A shielding material can be specified between each source-receptor pairfor external gamma dose calculations. The user can select shielding material fromeight different material types. Seven exposure pathways are considered in theRESRAD-BUILD code: (1) external exposure directly from the source,(2) external exposure to materials deposited on the floor, (3) external exposuredue to air submersion, (4) inhalation of airborne radioactive particulates,(5) inhalation of aerosol indoor radon progeny and tritiated water vapor,(6) inadvertent ingestion of radioactive material directly from the source, and(7) ingestion of materials deposited on the surfaces of the building compartments.Various exposure scenarios may be modeled with the RESRAD-BUILD code.These include, but are not limited to, office worker, renovation worker,decontamination worker, building visitor, and residency scenarios. Bothdeterministic and probabilistic dose analyses can be performed with RESRAD-BUILD, and the results can be shown in both text and graphic reports.

1-2

1-3

1 INTRODUCTION

Argonne National Laboratory has developed the computer code RESRAD for theU.S. Department of Energy (DOE) to evaluate residual radioactive material in soil(Yu et al. 1993, 2001). The RESRAD code implements the DOE requirements described inChapter 4 of DOE Order 5400.5 (DOE 1990). Many sites that are contaminated with radioactivematerial in soil also have contamination inside the buildings on the site. DOE Order 5400.5provides generic surface contamination guidelines that are applicable to building structures andequipment. Those generic contamination guidelines, in general, are not dose-based. ArgonneNational Laboratory, sponsored by the DOE, has developed a methodology for assessingradiological doses resulting from the reuse of surface-contaminated material and equipment(Cheng et al. 2000). This methodology has been coded in a computer program called RESRAD-RECYCLE. To evaluate indoor building surface contamination, a detailed modeling of therelease mechanisms and transport of contaminants in the indoor environment is needed. Suchmodeling would be especially useful because buildings (like soil) vary from site to site; thebuilding structural materials may be different; the size and air exchange rate of the buildings androoms within them may be different; and the contamination inside the buildings may vary in size,thickness, and shape. The RESRAD-BUILD computer code was developed on the basis of thesefactors, and it considers all the potential exposure pathways to an individual in a contaminatedbuilding.

The RESRAD-BUILD computer code is a pathway analysis model developed to evaluatethe potential radiological dose incurred by an individual who works or lives in a buildingcontaminated with radioactive material. The radioactive material in the building structure can bereleased into the indoor air by mechanisms such as diffusion (radon gas and tritiated water),mechanical removal (decontamination activities), or erosion (removable surface contamination).The transport of radioactive material within the building from one compartment to another iscalculated with an indoor air quality model (see Appendix A). The air quality model evaluatesthe transport of radioactive dust particulates and radon progeny due to (1) air exchange betweencompartments and with outdoor air, (2) the deposition and resuspension of particulates, and(3) radioactive decay and ingrowth. RESRAD-BUILD can model up to three compartments in abuilding, thereby making it possible to evaluate situations ranging from a one-room warehouse toa three-story house, for example.

The design of RESRAD-BUILD is similar to that of the RESRAD code: the user canconstruct the exposure scenario by adjusting the input parameters. Typical building exposurescenarios include long-term occupancy (resident and office worker) and short-term occupancy(renovation worker and visitor). The long-term occupancy scenarios are usually low releasescenarios, whereas short-term occupancy scenarios may involve a high release of contaminantsin a short time period. Up to 10 receptor locations and 10 distinct source locations can be inputinto the RESRAD-BUILD code to calculate dose in a single run of the code. The calculated dosecan be the total (individual) dose to a single receptor spending time at various locations or thetotal (collective) dose to a workforce decontaminating the building. If a building is demolished,the RESRAD computer code may be used to evaluate the potential dose from the buried material.

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The RESRAD-BUILD code considers seven exposure pathways: (1) external exposuredirectly from the source, (2) external exposure to materials deposited on the floor, (3) externalexposure due to air submersion, (4) inhalation of airborne radioactive particulates, (5) inhalationof aerosol indoor radon progeny (in the case of the presence of radon predecessors) and tritiatedwater vapor, (6) inadvertent ingestion of radioactive material directly from the source, and(7) ingestion of materials deposited on the surfaces of the building compartments. A detaileddiscussion of exposure scenarios and pathways is presented in Section 3.

The RESRAD-BUILD code can compute the attenuation due to a shielding materialbetween each source-receptor combination when calculating the external dose. The user canselect the shielding material from eight material types and input the thickness and density of theshielding material. The user may also define the source as a point, line, area, or volume source.Volume sources can be composed of up to five layers of different materials, with each layerbeing homogeneous and isotropic.

The radionuclides included in the RESRAD-BUILD code are similar to those included inthe RESRAD code. Currently, the RESRAD-BUILD database contains 67 radionuclides, andadditional radionuclides are being added. All these radionuclides have a half-life of six monthsor longer, and they are referred to as principal radionuclides. It is assumed that the short-liveddecay products with half-lives of six months or less, referred to as the associated radionuclides,are in secular equilibrium with their parent (principal) radionuclides. For the 67 principalradionuclides in the current RESRAD-BUILD database, there are 53 associated radionuclides.Therefore, a total of 120 radionuclides are available in RESRAD-BUILD Version 3. A detailedlist of these radionuclides can be found in Table 3.1 of the RESRAD User’s Manual(Yu et al. 2001).

The information presented in this manual is organized as follows:

• Descriptions of buildings, sources of contamination, and receptors exposed toradiation — Section 2;

• Exposure pathways and scenarios for building contamination — Section 3;

• Description of the RESRAD-BUILD code and instructions for its use —Section 4;

• Verification of the RESRAD-BUILD code — Section 5;

• Models, formulas, and the database used in RESRAD-BUILD code —Appendixes A through H;

• Uncertainty analysis — Appendix I; and

• Detailed discussion of parameters used in the RESRAD-BUILD code —Appendix J.

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2 DESCRIPTIONS OF BUILDINGS, SOURCES, AND RECEPTORS

The RESRAD-BUILD code is designed to evaluate the radiological doses to individualswho live or work inside a building that is contaminated with radioactive material. Thecontamination could be (1) on the surface of the floors, walls, or ceiling; (2) within the buildingmaterial, such as in the drywall, concrete floors, steel I-beams, metal pipes, or wires; and(3) accumulated inside the building, such as in the air exchange filter or drain. RESRAD-BUILDcan model up to three compartments in a building. A compartment can be one room or severalrooms on the same floor with free air exchange among the rooms. External radiation penetratingthe walls, ceilings, or floors is calculated on the basis of the user input for shielding materialtype, thickness, and density. Internal (inhalation and ingestion) exposures are calculated on thebasis of an air quality model that considers the air exchange between rooms and with outdoor air.

The RESRAD-BUILD code can be applied to evaluate the potential exposure of anindividual standing or working outside a contaminated building by assuming that the outdoorspace is a large room (compartment) adjacent to the contaminated building. The building, sourceof contamination, and receptors modeled in the RESRAD-BUILD code are discussed in detail inthe following subsections.

2.1 BUILDING DESCRIPTION

In the RESRAD-BUILD model, the building is conceptualized as a structure composedof up to three compartments. It can be a one-room warehouse, a two-room house or apartment, athree-room ranch house, a three-story office building, or a two-story house with a basement. Airexchange is assumed between compartments 1 and 2 and compartments 2 and 3 but not betweencompartments 1 and 3. All compartments can exchange air with the outdoor atmosphere. It isalso possible to set air exchange between a compartment and the outdoor atmosphere to zero, forexample in a case of 2-story house with a basement when there is no air exchange between thebasement and the outdoors. An air quality model was developed to calculate the contaminantconcentration in each compartment. A detailed description of the air quality model is presentedin Appendix A.

Typical building geometries that can be modeled by the RESRAD-BUILD code areillustrated in Figure 2.1. A coordinate system is used in RESRAD-BUILD to define the locationof the sources and receptor points inside the building. The origin and axes of the coordinatesystem can be at any location and in any direction. The origin, however, is usually located at thebottom left corner of the lowest level, with the x-axis measuring the horizontal distance to theright of the origin and coinciding with the bottom edge of the compartment (see Figure 2.2); they-axis being perpendicular into the building; and the z-axis measuring the vertical distance andcoinciding with the left edge of the building.

The user can specify the locations of the sources and receptors and the amount of time thereceptor spends in each compartment, so the radiological dose to the receptor can be calculated

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3-Room House2-Room House1-Room Warehouse

2-Story House 2-Story Building with2 Rooms on the First Floor

2-Story Housewith Basement

(No air exchangebetween basement

and outdoors.)

3-Story House

CYA10101

indicates air exchange

FIGURE 2.1 Vertical View of Possible Building Geometries for the RESRAD-BUILD Code

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Origin

z

x

y

CYA10102

FIGURE 2.2 Example of a Coordinate System Used in the RESRAD-BUILD Code

for any type of building use, including residential, commercial, or industrial. Therefore, thebuilding model approach used in RESRAD-BUILD is quite flexible.

2.2 SOURCE DESCRIPTIONS

The building is assumed to be contaminated with radioactive materials located at adefined number of places within the structure of the building. Each contaminated location isconsidered a distinct source, and as many as 10 sources can be specified in a single run ofRESRAD-BUILD. Depending on its geometric appearance, the source can be defined as avolume, area, line, or point source. The distinctions among these types of sources are ratherarbitrary and reflect the modeling objective of simplifying the overall configuration wheneverjustifiable. The proper classification of each source is left to the user’s best judgment. Forexample, if the distance between the receptor and a small area source is much greater (say, fivetimes greater) than the largest dimension of the area source, then this small area source may bemodeled as a point source.

In general, each source is initially characterized by defining its type, the compartment inwhich it is located, and the coordinates of its center, according to the system of coordinates usedfor the building compartments (see Figure 2.2). The number of different radionuclides and theirinitial concentrations are also defined for each source. Depending on the type of the source, twoother geometric parameters may also be defined: the area/length and the direction of the source.For either a volume or a surface source, the area is defined as the surface area of the sourcefacing the open air; the area is assumed to be circular. Source direction is defined as the vector

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perpendicular to the exposed area. This direction should be coincident with one of the axes (x, y,or z). For a line source, the length parameter is defined as the length of the segment of lineforming the source, and direction is given by the direction of the line itself. Again, the directionof the line source must be coincident with an axis. For a point source, neither the direction northe area or length parameter is used.

Mechanical removal and erosion of the source material, when its surface is exposed toopen air, will result in the transport of part of its mass directly into the indoor air environment,resulting in airborne contaminants. Because of the air exchange processes among allcompartments of the building, the airborne particulates being loaded into the indoor air of thecompartment are then transported to the indoor air of all compartments of the building.

A contaminated area in the building should be considered a volume source if it can beclearly represented in a three-dimensional configuration. A segment of a wall in the building,contaminated with radioactive materials, is an example of a possible volume source. The volumesource could be located entirely within one compartment, such as in an external wall, or it couldbe located at the boundaries of the compartment, such as in the floor/ceiling or in the wallseparating two compartments. If the volume source is located at the boundary between twocompartments, it could have two faces, one exposed to the open air of each compartment. In thiscase, the volume source could release radon and tritiated water to both compartments but releasecontaminated particulates to the primary side only. Currently, the releases of tritiated water areestimated for the primary side only. The radon releases are from both sides, but the fluxes go inthe same compartment as the source. In the RESRAD-BUILD model, the volume source can becomposed of up to five distinct parallel regions (or layers) located along the direction parallel tothe partition, each consisting of homogeneous and isotropic materials. Each layer is defined byits physical properties, such as thickness, density, porosity, radon effective diffusion coefficient,radon emanation fraction, erosion rate (of the surface closest to the origin), and concentration ofradioactive contaminants. The definition of a volume source must also identify to whichcompartments the faces of the source are exposed. Finally, the rate of inadvertent ingestion ofloose materials directly from the source must be defined.

Definition of a surface source is considered in those cases of surface contamination inwhich the thickness of the contaminated layer is considerably smaller than the affected areaexposed to open air. An example would be a spill of radioactive materials over an area ofrelatively large dimensions, with very little penetration of the spilled substance into the matrix ofthe contaminated medium. Each surface source is associated with a removable fraction, a timefor source removal (source lifetime), a release fraction of material to the indoor air (air releasefraction), and a direct ingestion rate. The unit of radionuclide concentration for area sources usedin RESRAD-BUILD is picocuries per square meter (pCi/m2) or becquerels per square meter(Bq/m2).

A line source can be defined for those cases in which one dimension, such as length, isclearly larger than any other dimension of the source. A pipe carrying radioactive materials, orthe wall/floor joint edge with accumulated contaminated substances, could be considered a linesource. Parameters used to characterize the line source are similar to those for the area source.The unit of radionuclide concentration for line sources is pCi/m or Bq/m.

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Contaminated locations in the building where the radioactive materials are concentratedin regions of small dimensions (compared with the dimensions of the compartment and thedistance to the receptor) could be approximated as point sources. Parameters used to characterizepoint sources are similar to those for the area and line sources. The unit for point sources is pCior Bq.

2.3 RECEPTOR DESCRIPTIONS

The receptors considered in the RESRAD-BUILD model include office worker, resident,industrial worker, renovation worker, building visitor, or any individual spending some timeinside the contaminated building. The RESRAD-BUILD code was designed with flexibility andsimplicity in mind, so that the model can simulate diverse exposure scenarios, such as officework, building cleaning and maintenance work, building renovation, building visiting, andcontinuous residency. The exact location (coordinates) of the receptor is required to calculateexternal exposure. The receptor location should be the midpoint of the person. For example, ifthe receptor is standing on a contaminated floor, the receptor location should be 1 m above thefloor. For other pathways, only the information about the room in which the receptor is located isrequired by the code, because the air quality model assumes that the air is homogeneously mixedin each compartment. To calculate the external dose, the shielding material type and its densityand thickness need to be input into the code, in addition to the receptor location. The orientationof the receptor to the source may affect the external dose. For example, when the receptor isfacing the source (anterior-posterior [AP]), the external dose may be greater than it is when thereceptor is in the rotational or back-to-the-source (posterior-anterior [PA]) orientation. In mostsituations, the receptor is moving around and is not in a fixed position facing the source.Therefore, the external dose conversion factors (DCFs) for rotational orientation are used in theRESRAD-BUILD code.

Up to 10 receptor points can be specified in the RESRAD-BUILD code. The timefraction spent at each receptor point needs to be input. The total time fraction can exceed unity.These criteria allow RESRAD-BUILD to evaluate total (collective) worker dose as well as thetotal individual dose in a single run of the code.

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3-1

3 DESCRIPTIONS OF EXPOSURE SCENARIOS AND PATHWAYS

3.1 EXPOSURE SCENARIOS

Before a contaminated building can be released for use without radiological restrictions,the potential future use of the building must be evaluated. That potential future use of a buildingdepends on many factors, such as the current use, age, conditions, location, and size of thebuilding and the extent of contamination.

The potential uses of a building are referred to as exposure scenarios, which can beclassified into two major categories: building occupancy and building renovation. Buildingoccupancy scenarios include residents, office workers, industrial workers, and visitors. Buildingrenovation scenarios include decontamination workers, building renovation workers, andbuilding demolition workers. The building occupancy scenarios usually involve rather long-termchronic exposures, whereas building renovation scenarios usually involve short-term exposures.Building decontamination and renovation activity scenarios usually result in a higher amount ofcontaminant removal than do building occupancy scenarios. However, decontamination andrenovation are usually performed under controlled conditions, and contaminated materials areremoved from the building. Therefore, the actual amount of contaminants released into theindoor air may or may not be greater than the amount that is released under building occupancyscenarios. The building occupancy scenarios may result in the release of contaminants into theair as a result of normal use and cleaning of the building, such as washing the walls orvacuuming the floors. Building renovation includes such activities as sanding a contaminatedfloor, chipping concrete, and removing or installing drywall.

The differences among these scenarios are associated with the exposure durations, theamounts of contaminants and the rates at which they are released into air, and the pathwaysinvolved. The RESRAD-BUILD code is designed to model all these exposure scenarios. If theuser inputs appropriate parameters for the exposure duration and amount and rate ofcontaminants released into the air and selects appropriate pathways, RESRAD-BUILD canmodel all scenarios. Input template files for the building occupancy and building renovationscenarios are provided in Section 3.3. If a building is demolished, the dose to workersdemolishing the building can be evaluated with the RESRAD-BUILD code. If the demolishedbuilding material is buried, the RESRAD computer code (Yu et al. 2001) can be used to evaluatethe dose for future use of the site. If building material (such as steel I-beams) is recycled, theRESRAD-RECYCLE code (Cheng et al. 2000) can be used to evaluate the dose to workers andthe general public.

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3.2 EXPOSURE PATHWAYS

The exposure pathways considered include external and internal exposure. Figure 3.1illustrates all the pathways considered in the RESRAD-BUILD code:

1. External exposure to penetrating radiation emitted directly from the source,

2. External exposure to penetrating radiation emitted from radioactiveparticulates deposited on the floors of the compartments,

3. External exposure to penetrating radiation due to submersion in airborneradioactive particulates,

4. Inhalation of airborne radioactive particulates,

5. Inhalation of aerosol indoor radon decay products and tritiated water vapor,

6. Inadvertent ingestion of radioactive material contained in removable materialdirectly from the source, and

7. Inadvertent ingestion of airborne radioactive particulates deposited on thesurfaces of the building.

The first three pathways would result in external exposure, and the last four would resultin internal exposure due to internal contamination of the exposed individual. In RESRAD-BUILD, the external radiation doses are evaluated as the effective dose equivalent, and theinternal exposure is evaluated as the committed effective dose equivalent (CEDE). The totalradiation dose, which is the sum of the external and internal doses, is expressed as the totaleffective dose equivalent (TEDE). The DCFs used for inhalation, ingestion, and externalexposures are discussed in detail in Appendixes D, E, and F, respectively.

Other possible exposure pathways to be considered in a radiological analysis of acontaminated building would include internal contamination due to puncture wounds and dermalabsorption of radionuclides deposited on the skin. However, the radiation doses caused by thesetwo pathways would be much smaller than the doses caused by the other potential pathwaysalready considered for most radionuclides (Kennedy and Strenge 1992). Therefore, dermalpathways are not included in the current version of RESRAD-BUILD. However, the dermalabsorption of tritium is considered by increasing the inhalation dose conversion factor by 50%.

3.3 INPUT DATA TEMPLATES

For both the building occupancy and building renovation scenarios, the external,inhalation, ingestion, and air submersion dose conversion factors are radionuclide specific. Thevalues are taken from the Federal Guidance Reports (FGR) 11 and 12 (Eckerman et al. 1988;

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FIGURE 3.1 Exposure Pathways Incorporated into the RESRAD-BUILD Code

Eckerman and Ryman 1993). The dose is calculated for one receptor only. The receptor is at thecenter of the floor at a height of 1 m. The critical group receptor occupies a room withcontaminated sources. For a site-specific analysis, the total number of sources, source types,source locations, room area, and room height should be site specific. Table 3.1 lists the keyparameters used in the building occupancy and building renovation scenarios. Only thoseparameters that would be different are listed, the other parameters are site specific or are kept atRESRAD-BUILD defaults. It is assumed that for the building occupancy scenario,contamination is only on the surface, while for the renovation scenario, contamination isvolumetric. Detailed descriptions of parameters and their distributions are given in Appendix J.The technical basis for calculating radiation doses for the building occupancy scenario and therelated parameter distributions are provided in Biwer et al. (2002).

External ExposureDirectly from the Source

Inhalation of IndoorRadon Progeny/Tritium

Inhalation of AirborneRadioactive Dust

External ExposureDue to Air Submersion

External Exposure Dueto Deposited Material

Ingestion of DepositedRadioactive Material

Ingestion of RemovableRadioactivity

Indoor Air Concentration of Radon Progeny/Tritium

Release Rateof Radon/Tritium

into Indoor Air

Radon/TritiumDiffusion

Indoor Airborne Concentrationof Radionuclides

Release Rate of

Radionuclidesinto Air

MechanicalRemoval of

Material fromthe Source

Surface

Concentration of Radionuclides in

Deposited Dust Particles

Rad

ioac

tive

Mat

eria

l Ins

ide

Bui

ldin

g

Resuspension

Deposition

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TABLE 3.1 Key Parameters Used in the Building Occupancy and Building Renovation Scenarios

Parameter Values

Parameter UnitBuilding

OccupancyaBuilding

Renovationb Remarks

Exposure duration days (d) 365.25 179.00 To match the occupancy period of 365.25 days in NUREG/CR-5512 building occupancy scenario (Beyeler et al. 1999) andrenovation period of 179 days in NUREG/CR-5512 buildingrenovation scenario (Wernig et al. 1999).

Indoor fraction −c 0.267 0.351 To match the 97.5 d/yr time in building in NUREG/CR-5512building occupancy scenario (Beyeler et al. 1999) and62.83 days spent in the building during renovation period inNUREG/CR-5512 building renovation scenario (Wernig et al.1999).

Receptor location m 0, 0, 1 0, 0, 1 At 1-m from the center of the source.

Receptor inhalation rate m3/d 33.6 38.4 For building occupancy scenario it matches with 1.4 m3/hbreathing rates in NUREG/CR-5512 (Beyeler et al. 1999) andfor building renovation scenario it matches with 1.6 m3/hbreathing rate of moderate activity given in the EPA ExposureFactor Handbook (EPA 1997).

Receptor indirect ingestion rate m2/h 1.12 × 10-4 0 Value for the building occupancy scenario is the mean valuefrom the distribution and for the building renovation scenario itis assumed the ingestion is only from the direct contact with thesource.

Source type − Area Volume For building occupancy scenario it is assumed thatcontamination is only on the surfaces, whereas for the buildingrenovation scenario contamination is volumetric.

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TABLE 3.1 (Cont.)

Parameter Values

Parameter UnitBuilding

OccupancyaBuilding

Renovationb Remarks

Direct ingestion rate 1/h (area)g/h(volume)

3.06 × 10-6 0.052 Calculated from the default ingestion rate of 1.1 × 10-4 m2/h inNUREG/CR-5512 building occupancy scenario (Beyeler et al.1999). The effective transfer rate from NUREG/CR-5512building renovation scenario for ingestion of loose dust to thehands and mouth during building renovation (Wernig et al. 1999).

Air release fraction − 0.357 0.1 For the building occupancy scenario, it is the mean value from theparameter distribution (Appendix J). For the building renovationscenario, a smaller fraction is respirable.

Removable fraction − 0.1 NRd 10% of the contamination is removable (NUREG/CR-5512building occupancy scenario default). The parameter is notrequired for the volume source.

Time for source removal orsource lifetime

d 10,000 NR Value for the building occupancy scenario is the most likely valuefrom the parameter distribution (Appendix J). The parameter isnot required for the volume source.

Source erosion rate cm/d NR 4.1 × 10-4 For the building renovation scenario, it is assumed that the totalsource thickness of 15 cm can be removed in 100 years ofbuilding life.

a Parameter values used in the building occupancy scenario.

b Parameter values used in the building renovation scenario.

c A dash indicates that the parameter is dimensionless.

d NR = parameter not required for the analysis.

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4-1

4 USER’S GUIDE

The RESRAD-BUILD computer code is designed to assess the radiological doses toindividuals who live or work in a building contaminated with radioactive material. Theconceptual model, with its underlying assumptions, and descriptions of the building, sources, andreceptors are presented in Section 2. Section 3 describes exposure scenarios and pathways. Amore specific and detailed description of the model used in RESRAD-BUILD is presented in theappendixes. This section describes the use of RESRAD-BUILD as follows:

• Section 4.1, Installation: Lists requirements and installation procedures forvarious distribution media.

• Section 4.2, Navigation and File Management: Describes how to move aroundthe interface to accomplish tasks and how to save input and output results.

• Section 4.3, Input Windows: Provides a closer look at the parameters on theinput windows.

• Section 4.4, Results Windows: Discusses how to find results in the textual andgraphical output.

4.1 INSTALLATION

Requirements for installation are as follows:

• Windows 95, 98, NT, XP, 2000, or later versions;

• Pentium-compatible processor;

• 16 MB of random access memory (RAM); and

• 16 MB of disk space.

• A printer driver must be installed, although a physical printer need not beattached.

To install from CD-ROM:

• Insert the CD-ROM into the CD-ROM drive.

• Click Install Product.

• Click Install RESRAD-BUILD.

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• Enter the information requested by the standard installation program.

• After installation, a new RESRAD-BUILD icon will be placed in theRESRAD group. Double-clicking on this icon will start RESRAD-BUILD.

To install from the Web site:

• Register at the RESRAD Web site: web.ead.anl.gov/resrad/register.

• Download the latest RESRAD-BUILD self-extracting executable to yourcomputer.

• Run this executable.

• Enter the information requested by the standard installation program.

• After installation, a new RESRAD-BUILD icon will be placed in theRESRAD group. Double-clicking on this icon will start RESRAD-BUILD.

To uninstall RESRAD-BUILD:

• Click on Start.

• Click on Control Panel.

• Click on Add/Remove Programs.

• Click on RESRAD-BUILD 3.X for Windows.

• Click on Change/Remove.

• Complete uninstall process.

4.2 NAVIGATION AND FILE MANAGEMENT

The main window that appears when RESRAD-BUILD is started is shown in Figure 4.1.This window contains six input “subwindows”: Case, Building Parameters, Radiological Units,Receptor Parameters, Shielding Parameters, and Source Parameters. These six windows showsome of the major input parameters necessary for RESRAD-BUILD. Three of the windows(Case, Building, and Source Parameters) contain buttons to access more detailed input windows.The Shielding Parameters window contains buttons to facilitate specification of multiple shields.

The main window contains a menu and toolbar. The File menu option contains thestandard functions for file management, which pertain to the input file only. The output files are

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FIGURE 4.1 Main Menu

saved under a standard name for each run and are automatically overwritten unless they areexplicitly saved by using the Save All command in the Output Report Viewer. The File menualso includes a Run option, which starts the calculations after all the parameters have beenspecified. These functions are also available by activating the first four toolbar buttons.

Users can also open previously saved input files with the File/Open command. TheRESRAD-BULD input files have a .BLD file extension by default. To share files, fordeterministic cases, the .BLD file is all that is required. For probabilistic cases, an additional filewith an .LHS file extension is automatically saved whenever the .BLD file is saved.

The View menu option allows the user to toggle the visibility of certain windows,including the output windows, graphic output windows, three-dimensional (3-D) display, anduncertainty window. These functions are also available by activating the next four toolbarbuttons.

The Modify menu option allows the user to add and delete receptors and sources.Shortcut keys are defined for these functions, but no toolbar buttons are defined.

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Context-specific help can be viewed by clicking on the Help menu or the last toolbarbutton on the right, or by pressing the F2 key while highlighting an input textbox (Figure 4.1).

Template files can also be saved with a .TEM extension. Template files are useful whensaving a particular scenario class, such as a building renovation scenario. Two template files forbuilding occupancy and building renovation scenarios are distributed with the RESRAD-BUILDcode.

4.3 INPUT WINDOWS

4.3.1 Case Window

The Case Window (Figure 4.2) allows for a user-specified title that is placed at the top ofall output report pages. Two of the three exposure time parameters appear in the Case window.Exposure Duration is the period of time over which the exposure takes place. The dose will beintegrated over this time period. Discussion on the integrated dose is provided in Appendix H.Indoor fraction specifies the fraction of the exposure duration that a receptor is inside thebuilding. The third time parameter, Time Fraction, appears in the Receptor Parameters window(Figure 4.8, which appears later in Section 4.3.3). This allows receptor-specific time fractions tobe entered. The time a receptor spends at a given location is the product of these three exposuretime parameters.

The total time spent on site is specified in days. The calculated radiological doserepresents the total dose received during the exposure time. RESRAD-BUILD also calculates adose rate in terms of dose per year.

RESRAD-BUILD follows the decay, ingrowth, and erosion of the contaminated materialover time. The user can select up to 10 times to be evaluated. The model estimates doses for the

FIGURE 4.2 Case Window

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user-specified scenario for each time by calculating the time-integrated dose of the sourcestarting from the specified evaluation time for the exposure duration. This allows the user todetermine the estimated dose at the initial characterization and at later times (e.g., at loss ofinstitutional control or expected demise of the building).

By pressing the Evaluation Times button, the user can specify the times in the EvaluationTimes window (Figure 4.3) by either entering the times in the text boxes or by moving the clockicons. The estimate for the initial time, time zero, is automatically included. The user can selecteither 1, 2, 3, 5, 9, 17, 33, 65, 129, or 257 as the number of points to calculate the time-integrateddose. If the user selects 1, the instantaneous dose at the user-specified time is calculated. The useof integration points is further discussed in Appendix H.

4.3.2 Building Parameters

The second input form in the modify data series represents the characteristics of thebuilding (Figure 4.4). The conceptual building model consists of one to three rooms. The usermust enter the area and the ceiling height of each room. These parameters are used in the airquality model. To solve the air quality model, the user must enter the average building air-exchange rate for the one-room model. For the two- and three-room models, the user must enteradditional parameters for each additional room: the outdoor inflow rates for the rooms, the flowbetween adjacent rooms 1 and 2, and the flow between adjacent rooms 2 and 3. It is assumed thatno direct airflow occurs between rooms 1 and 3. To solve the deposition model, a depositionvelocity and resuspension rate are required, which are assumed to be the same in each room.

4.3.2.1 Room Details for One-Room Model

For the one-room model (Figure 4.5), the only airflow parameter necessary is the total airexchange rate.

4.3.2.2 Room Details for Two-Room Model

For the two-room model (Figure 4.6) the airflow parameters necessary are the outdoorinflow in both rooms and the flow between the two rooms. The full airflow then can be solved ifthe parameters entered satisfy certain conditions that guarantee a positive exchange of airbetween the rooms. These conditions are discussed in the air quality model in Appendix A.

4.3.2.3 Room Details for Three-Room Model

For a three-room model (Figure 4.7), the airflow parameters necessary are the outdoorinflow in all rooms and the flow between the adjacent rooms. It is assumed that there is no direct

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FIGURE 4.3 Evaluation Times Window

FIGURE 4.4 Building Parameters Window

FIGURE 4.5 Room Details for One-Room Model

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FIGURE 4.6 Room Details for Two-Room Model

FIGURE 4.7 Room Details for Three-Room Model

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inflow between room 1 and room 3. The full airflow then can be solved if the parameters enteredsatisfy certain conditions that guarantee a positive exchange of air between the rooms. Theseconditions are discussed in the air quality model in Appendix A.

4.3.3 Receptor Parameters

The Receptor Parameters window (Figure 4.8) allows the user to specify the exposurecharacteristics of an individual. Although multiple receptors can be specified, the ReceptorParameters window shows input only for the individual specified by the Receptor #. Multiplereceptors could be interpreted as many different individuals in a room or as one individual whospends time at many different locations. The total time an individual spends at a particularlocation is the product of the exposure duration, indoor fraction, and the time fraction. Eachreceptor point is specified by the room, location, and fraction of the time that an individualspends at each location. The ingestion rate applies to the ingestion pathway of incidental dustingestion. The breathing rate must also be specified.

The location of the receptor is the absolute coordinate of the receptor midpoint locationaccording to some origin chosen by the user. The same reference origin is used for all receptorsand sources. For example, the receptor location should be 1 m above the absolute location on thefloor where the receptor is standing. This information is important for the direct externalexposure pathway only. The other pathways only require the room locations of the receptor andthe source.

FIGURE 4.8 Receptor ParametersWindow

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4.3.4 Shielding Parameters

Although the locations of the source and receptor points are known, the external pathwayalso requires information about the shielding between them. This information is gathered in theShielding Parameters window (Figure 4.9). The RESRAD-BUILD model is simplified so that theuser specifies just one average shield between each source-receptor point pair. This shielding ischaracterized by a material type, thickness, and density. The possible material types includeconcrete, water, aluminum, iron, copper, tungsten, lead, and uranium. The View Table button onthis window opens a screen that allows the user to view and modify the shielding between eachreceptor and source (Figure 4.10). The Shielding Parameters window always displays theshielding parameters for the receptor and source that are being viewed in their respectivewindows. The Copy Shielding button in this window opens a screen that allows the user to copythe current shielding properties of a receptor or a source to multiple receptors and sources(Figure 4.11).

4.3.5 Source Parameters

The Source Parameters window collects data on the source type and location(Figure 4.12). The location of the source includes the room and the coordinates of the centerpoint of the source. The location of the source center point is the absolute coordinate accordingto some origin chosen by the user. This reference origin must be used to specify the receptorlocations also. This information is important for the direct external-exposure pathway only. Theother pathways require only the room location of the receptor and the source.

The source details are specified in one of the secondary windows (input forms) bypressing the button with the radiation symbol in the main menu. The secondary forms(Figures 4.13 through 4.16) request information about radon release (if applicable), size,removable fraction, air release fraction, and radionuclide contamination of the source. Forexternal dose calculations, the volume and area sources are assumed to be circular. Fornonvolume sources with a radon source present, the radon release fraction is required.

FIGURE 4.9 Shielding ParametersWindow

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FIGURE 4.10 Source-Receptor Table Window

FIGURE 4.11 Copy Shielding Window

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FIGURE 4.12 Source ParametersWindow

FIGURE 4.13 Volume Source Detail Window

For the volume sources, an additional form on the properties of the source (Figure 4.17)needs to be completed. The source is modeled as a number of distinct regions. The properties ofeach region include density, porosity, radon emanation fraction, radon diffusion coefficient,thickness, and the erosion rate in the region. If there is more then one region, Region 1 is definedas the region closest to the origin. For the tritium volume source, a separate source needs to beentered, with tritium as the only contaminant. The property window for a tritium source is shownin Figure 4.18.

A 3-D display of source and receptor objects (Figure 4.19) can be viewed andmanipulated by selecting the 3-D View option through the View/3-D Display menu options orthe 3-D Display toolbar button. Each type of object is represented by a different icon: grayperson for a receptor, square for a volume source, circle for an area source, line for a line source,and ball for a point source. Each object is displayed in the 3-D x, y, and z coordinate space. The

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FIGURE 4.14 Area Source Detail Window

FIGURE 4.15 Line Source Detail Window

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FIGURE 4.16 Point Source Detail Window

projection on the x-y plane is indicated by an oblique crosshair (pedestal). The height(z dimension) is represented as a column from the pedestal. The scale (in meters) of each of theaxes is given by the number above the Reset Scale button. To change the scale, the user enters anew number in the box and presses the Reset Scale button. The objects can also be manipulatedin 3-D by clicking on the pedestal or object and then dragging. Dragging the pedestal changesthe x and y coordinates. Dragging the object changes the z coordinate. The object number is alsodirectly displayed on the object (e.g., the second receptor is indicated by the number 2 in themiddle of the gray bubble person icon). The room assignment can also be determined by thecolor (red, green, or blue) of the number.

4.3.6 Radiological Units

Users are able to specify the units they wish to input into the activity concentration andview the resultant dose equivalent (Figure 4.20). The primary units for activity concentrationinclude Ci (curies) Bq (becquerels), dpm (disintegrations per minute), and dps (disintegrationsper second), while the primary units for dose equivalent include rem and Sv (sievert). Inaddition, users can select any metric prefix to be used for Ci, Bq, rem, and Sv. The allowedprefixes are as follows:

E exa 1 × 1018 d deci 1 × 10-1

P peta 1 × 1015 c centi 1 × 10-2

T tera 1 × 1012 m mili 1 × 10-3

G giga 1 × 109 µ micro 1 × 10-6

M mega 1 × 106 n nano 1 × 10-9

k kilo 1 × 103 p pico 1 × 10-2

h hecto 1 × 102 f femto 1 × 10-15

none 1 a atto 1 × 10-18

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FIGURE 4.17 Nontritium Volume Source WallRegions Window

FIGURE 4.18 Tritium Volume Source Parameters Window

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FIGURE 4.19 Interactive 3-D Display Window

FIGURE 4.20 Radiological Units Window

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Previously entered concentrations are automatically adjusted when the activity units arechanged. The dose units in the report are fixed when the case is run.

4.4 RESULTS WINDOWS

The user must select the Run option from the File menu (or use the toolbar button thatlooks like the space shuttle) to calculate the dose estimate for the case that has been set up. Whilethe calculations are taking place for the deterministic analysis, the Run window (Figure 4.21) isdisplayed. This window contains (1) a short feedback line, (2) the amount of time spent so far onthe calculation, and (3) a button to cancel the current calculation and return to the main userinterface. After the calculation is complete, the report file is automatically opened in the reportviewer. (Note: RESRAD-BUILD can also be run from a DOS prompt or in batch mode. To dothis, create an input file, filename.BLD, and then issue the DOS command RESBMAIN.EXEfilename.BLD.)

4.4.1 Text Output

A report file named RESRADB.RPT (Figure 4.22) is generated each time RESRAD-BUILD is executed. This contains a complete input table and dose estimates for each time,broken into details by pathway, nuclide, source, and receptor. The Report Viewer may beaccessed at any time from the menu and toolbar. To move between reports, select File/Openfrom the main menu. To move within a page, use the scroll bars. There are many ways to movefrom page to page within the report:

• Enter the page number in the page text box and press return.

• Pull down the page list and click on the desired page.

• Advance a page by pressing the Page Down key or by clicking on the doubledown arrows.

• Go back a page by pressing the Page Up key or by clicking on the double uparrows.

FIGURE 4.21 Window Displayed during Calculations

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FIGURE 4.22 Output Report

Two other text files also contain calculation results. The file named Diag.out containssome intermediate calculation results, such as the airflow matrix and air concentrations fromeach source for each time. The file named resradb.grf contains a comma-delimited set of doseestimate details by source, parent radionuclide, progeny radionuclide, receptor, time, andpathway. These data can be copied into a spreadsheet or database for further analysis.

Every time a calculation is run, the previous reports and graphics files are overwritten.The results can be saved under different names, thus allowing for later retrieval.

• To save all files: Select File/Save All under the View menu. This option savesall textual reports to files. If the input filename is xxxx.BLD, the report issaved as xxxx.rpt.

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• To save the open report: Select File/Save under the View menu. This optionprompts the user for a name under which to save the currently displayedreport.

Printing is done in the standard way:

• To set up the printer: RESRAD-BUILD uses the standard Windows printer.The setup for the printer can be accessed through the File/Printer/Setup menuoption. Options to be selected include the printer, paper size, and paperorientation.

• To print: Select the File/Print menu option or press the printer icon button. Adialogue box lets you print the whole report, sets of pages, or the currenthighlighted text.

4.4.2 Graphic Output

The user may view results of RESRAD-BUILD output graphically by creating chartswith the RESRAD-BUILD Graphics Wizard, as shown in Figure 4.23. Enter the graphics wizardprogram either by clicking Standard Graphics from the View menu or by pressing the green-colored graph icon located on the toolbar.

Once the graphics wizard opens, the user can create a new graph from one of three charttypes: line, bar, or stacked. Line charts are most informative when one wishes to view resultsover many user-specified times. Bar and stacked charts are similar except stacked charts areuseful to display the total dose for a specific set of groupings. Bar charts provide an excellentway to display dose subtotals for specific groupings. After selecting the chart style, the user mustpress the Next button to display the selected chart.

When bar and stacked charts are selected, the user can select up to two categories for thex-axis (primary and secondary axis). For example, a user may wish to view the dose to eachreceptor for every pathway for a specific radionuclide and a specific source. In this case, the twocategories on the x-axis would be receptor (primary axis) and pathway (secondary axis).Figure 4.24 illustrates such a case. By selecting different primary and secondary axes, the usercan plot the results from many different points of view. For example, a user may want todetermine which nuclide-pathway combination contributes the most dose to a particular receptorat a given time. In this case, the primary axis would be radionuclide and the secondary axiswould be pathway. Figure 4.25 illustrates such a graph. This flexibility allows users to analyzethe results from a RESRAD-BUILD calculation in much greater detail than what is possible withthe text-based report alone. All charts can be printed with the File/Print menu option or bypressing the printer icon button. As an added feature, results from the RESRAD-BUILDGraphics Wizard can be exported to Microsoft Excel for further analysis.

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FIGURE 4.23 RESRAD-BUILD Graphics Wizard Window

FIGURE 4.24 Stacked Chart Showing the Dose to Each Receptorfor Each Pathway for Source 1

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FIGURE 4.25 Bar Chart of Dose to Receptor 3 for Each Radionuclideand Pathway Combination

4.5 PROCEDURES FOR USING PROBABILISTIC ANALYSIS

The procedures for using probabilistic analysis with the RESRAD-BUILD codes are asfollows:

• Run the standard software interface to set deterministic values for allparameters not involved with probabilistic analysis.

• Set the probabilistic analysis by finding parameters in the standard interfaceand pressing the F8 key. The probabilistic input window with four tab screensthen appears. The parameter is automatically added, with its defaultdistribution (if available), to the list of parameters for probabilistic analysis.The default distribution can be replaced with the site-specific distribution.

• Run the case. The standard deterministic calculations are performed first, thenthe probabilistic calculations begin. The estimated time for completion iscontinually updated and displayed.

• After the calculations are completed, the interactive output window forcreating tables and graphics appears. Access is available to both the textualreport and the detailed data dump files containing the results.

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The probabilistic modules have been designed to be flexible and quite independent of theoriginal RESRAD-BUILD application, yet easily applied and integrated with the application andable to use previously written software for Latin hypercube sampling (LHS) and correlationanalysis.

4.5.1 Input Window

The input window has four tabs that cover aspects of the sample specification, parameterdistributions, input rank correlations, and output specifications (Figure 4.26). This window isdisplayed by choosing either to add or modify probabilistic analysis for a parameter or to viewthe probabilistic input from the View menu on the main menu.

Uncertainty analysis can be turned off while yet preserving other settings by selecting the“Suppress uncertainty analysis this session” option at the bottom of this window.

4.5.1.1 Sample Specifications

The general sampling requirements, including the number of samples and the techniqueused to generate and correlate samples, are specified in the Sample Specifications tab

FIGURE 4.26 Sample Specifications Tab Screen

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(Figure 4.26). Information about the possible selections are shown in the right frame of the tab.Up to 2,000 observations can be specified. There is no software limit on the number ofrepetitions, although the memory available on the computer determines an effective limit.

• Sampling Technique: The Latin hypercube option splits the distribution to besampled into a number of equally probable distribution segments (the numberis equal to the desired number of observations) and obtains one sample atrandom from within each segment. This process ensures that the samplescover the entire range of the distribution. The Monte Carlo option obtains thespecified number of samples randomly from within the whole distribution.

• Grouping of Observations: The Correlated or Uncorrelated option orders thesamples for each variable so that (1) the correlations between the specifiedvariables are as close as possible to the specified input correlations and (2) thecorrelation between the variables that are not specified to be correlated are asclose to zero as possible. The Random option groups the variables in the orderthat they were obtained. It is possible that some of the variables so sampledwill be correlated just by chance.

4.5.1.2 Parameter Distributions

The Parameter Distributions tab screen (Figure 4.27) allows the user to view and edit allcurrently specified parameter distributions for probabilistic analysis. The parameters are listed inthe left frame. The detailed distribution properties are shown in the right frame.

• Navigation: Navigation to other parameter distributions is achieved by eitherclicking on the parameter in the left frame or using the Up-Down arrow buttonin the right frame.

• Variable Description List for Probabilistic Analysis: The list of the currentlychosen parameters (variables) is shown in the left frame. Clicking on one ofthe variables shown under the Variable Description heading causes thecomplete distribution properties for that variable to appear for review andediting on the right. Up to 250 variables can be chosen for probabilisticanalysis.

• Statistics of Uncertain Variable: The properties displayed are the distributiontype and the statistical parameters of the specific distribution. In the exampleshown in Figure 4.27, the statistical parameters are for the triangulardistribution, that is, the minimum, mode, and maximum. The changes that theuser makes to a distribution are automatically saved. However, if after makingchanges, the user wishes to restore the default distribution for this parameter,Restore Default can be selected. The user can also remove the parameter fromfurther probabilistic consideration by clicking on the Remove parameter button.A plot of this distribution is created if the “Help” button is pressed.

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FIGURE 4.27 Parameter Distributions Tab Screen

4.5.1.3 Input Rank Correlations

The Input Rank Correlations tab screen (Figure 4.28) allows the user to view and edit allcorrelations among input parameters for probabilistic analysis. The paired parameters withnonzero correlations are listed in the left frame. Correlations can be modified, added, or deletedin the right frame.

• Navigation. The user can select an existing correlation pair by clicking on itsrow in the left frame. New pairs are chosen in the right frame by selecting thetwo variables. The edits in this frame are incorporated after the user clicks onthe Update Correlation table button. The pair is removed by clicking on theRemove correlation button.

• Parameter List for Correlation. The currently chosen pairs of parameters arelisted in the left frame in a three-column table that shows the variable namesin the code and the correlation coefficients. By clicking on any element in anyrow of the table, the user can modify or delete the correlation in the rightframe. The range of correlation coefficients is from greater than –1.00 to lessthan 1.00. The correlation for all pairs not specified here is assumed to be 0.0.The user can check the results of the sampling correlation after the run has

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FIGURE 4.28 Input Rank Correlation Tab Screen

been completed. Full descriptions of the variables can be seen in the rightframe. If more parameters are chosen for correlation than fit in the window,the left frame becomes a scrolling table.

• Correlation Edit. The two correlated parameters and the correlation coefficientare shown and editable in the right frame. The user can also remove thecorrelation from further probabilistic consideration by clicking on the Removecorrelation button.

4.5.1.4 Output Specifications

The user selects from output options in the Output Specifications tab screen (Figure 4.29).More detailed output options (e.g., by pathway, nuclide, or user-specified times) take longer to run.

• Navigation. The output options are selected with the check boxes on the rightside of the screen. These options are the only inputs on this tab screen. Thecolumns on the right show what output options the user can obtain for each of

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FIGURE 4.29 Output Specifications Tab Screen

the checked options after running RESRAD-BUILD. The user is able tospecify and view these options from the interactive table and interactivegraphic screens. Various correlation types are available: partial correlationcoefficient (PCC), partial rank correlation coefficient (PRCC), standardizedpartial regression coefficient (SRC), and standardized partial rank regressioncoefficient (SRRC) (Iman et al. 1985).

4.5.2 Output Results

The case calculations are performed by clicking on the Run button. A pop-up window,shown in Figure 4.30, displays calculation progress feedback. The Cancel button in the lower rightof this window allows the user to stop the calculations at any time. When the calculations arecomplete, the deterministic summary report appears in the viewer window (Figure 4.22). Thisreport contains a complete list of all variables used in the case. This report contains the results fromthe deterministic calculations, which are therefore not related to the probabilistic analysis. Thereport can be accessed through the View option on the main menu.

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FIGURE 4.30 Window Displayed When Calculations Are BeingPerformed

The following sections discuss the variety of ways to access results.

The Interactive Output window contains interactive tabular and graphical results tofacilitate quick exploration of the data. The Uncertainty Report specifies the applied input anddetailed results. The LHS Report contains details of the sampling. The Correlate Output button inthe Navigator window allows the user to specify additional output after the main calculation hasbeen performed. Also, a formatted file (Access database) with the case name but a .BUOextension, gives the user access to the raw input and output data for specific analysis needs.

4.5.2.1 Interactive Output

The user can review the probabilistic inputs, including the Input Specifications tab screen(repetitions, observations, random seed; see Figure 4.31) and the Parameter Statistics tab screen(parameter distributions and input correlations; see Figure 4.32). The user can then select whattype of interactive output should be generated.

Results, the third tab screen, allows the user to explore text (Figure 4.33) and graphicalresults. For each table, the user can select a primary statistical object. The object contains the Doseat User Times. The primary statistical object has a series of secondary statistical objects. Thesecondary objects for the Dose at User Times contain all pathways, each individual pathway, allsources, each source, each nuclide, all nuclides, and each user time. After selecting the appropriatestatistical object, the user must specify the statistical property for analysis. The statistical propertyoptions contain either General Statistics or Percentile. The General Statistics Results table providesthe minimum, maximum, mean, and standard deviation and the 50th, 90th, and 95th percentile ofthe statistical object selected. The Percentile Results table provides the 5th through 95th percentileat every 5th percentile for the statistical object selected.

• Navigation. The user selects the type of output in the left frame by specifyingthe Statistical Object and Statistical Property. The Results table is shown inthe right frame. If the output is time-dependent, the user must then select fromthe previously entered specified times.

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FIGURE 4.31 Input Specifications Tab Screen

FIGURE 4.32 Parameter Distributions Tab Screen

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FIGURE 4.33 Text Results Tab Screen

• Statistical Object. The object contains the doses at user-specified times.

• Statistical Properties. The properties contain General Statistics (average,maximum, minimum, standard deviation), and Percentile. The right column ofthe Results table for these properties contain an estimate of how well thesevalues are known based on the variation within the repetitions. The numbersunder the +/- column are the standard deviation of the properties from therepetitions divided by the square root of the number of repetitions. They aremeasured in the same units as the property.

4.5.2.2 Interactive Graphical Output

RESRAD-BUILD output is also available for viewing in graphical plots (Figure 4.34).The plots include cumulative probability plots and scatter plots. The cumulative probability plotsprovide a plot of the statistical object selected versus the cumulative probability. The samestatistical object available for the tables is available for the cumulative probability plots. Thescatter plots provide a plot of the statistical object versus an input vector. Scatter plots should beused in conjunction with the correlation analysis to determine the correlation between the inputvector(s) and the output.

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FIGURE 4.34 Graphics Results Tab Screen

• Navigation. The user selects the type of output in the left frame of theGraphics Results tab screen (Figure 4.34) by specifying the Statistical Objectand Plot Type. The resulting graph is shown in the right frame. If the output istime-dependent, the user must then select from the previously enteredspecified times.

• Statistical Objects. The object contains the doses for individual pathways orfor all pathways at user-specified times for different receptors, sources, andradionuclides. The object can also select input parameter.

• Plot Type. The user can select output-input scatter plots and cumulativeprobability distribution plots.

4.5.2.3 Complete Tabular Report

The RESRAD-BUILD code generates two probabilistic report files. One pertains to theinput, and the other pertains to the output, as described below.

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• RESRAD-BUILD Input Report File. The Input Report File,EXAMPLE1.UN6, can be accessed via the View, Any file, or under All Files,among other ways. It is generated by the LHS program and is used byRESRAD-BUILD. It includes the following information for each repetition(or replication) requested by the user:

- The initial random seed.

- The number of probabilistic variables.

- The number of observations.

- The current repetition.

- A description of each probabilistic variable, the specified distribution,parameters defining the distribution, and the Label (FORTRAN name inRESRAD).

- The rank correlation matrix, if one was specified by the user.

- The adjusted rank correlation matrix, if the user-specified rank correlationmatrix is not positive definite.

- A list of all the input samples (or vectors) that were generated.

- A list of the rank of all the input samples that were generated.

- A matrix of correlations among the raw values of the variable generated bythe sampling program.

- A matrix of correlations among the rank of values of the variable generatedby the sampling program.

• RESRAD-BUILD Output Report File. The Output Report File (Figure 4.35)can be accessed via the View, Last Probabilistic Report, menu option. Thereport includes the following information:

- Table of Contents of the report.

- The number of sample runs, input parameter distributions specified, andthe statistical parameter associated with those distributions.

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FIGURE 4.35 Probabilistic Output Report File

- For each user-specified time:

♦ Statistics of the total dose (minimum, maximum, average, and standarddeviation) for all pathways and all radionuclides summed for eachsource and receptor.

♦ For each source and receptor, statistics of the dose (minimum,maximum, average, and standard deviation) for each pathway summedover the source radionuclides.

♦ For each source and receptor, percentile doses for each pathwaystarting at the fifth percentile, incrementing every fifth percentile tothe one hundredth percentile dose.

♦ For each source and receptor, statistics of the dose (minimum,maximum, average, and standard deviation) for each radionuclidesummed over the pathways.

♦ For each source and receptor, percentile doses for each radionuclidestarting at the fifth percentile, incrementing every fifth percentile tothe one hundredth percentile dose.

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- A table of regression and correlation coefficients between the total dose(summed over nuclides and pathways) and each of the probabilistic inputsfor each repetition. The coefficients included are the PCC, SRC, PRCC,and the SRRC. If selected by the user, these coefficients are available foreach individual pathway.

4.5.2.4 Complete Formatted Results File

The user has access to a complete formatted set of output results and input sample vectorsin Microsoft Access format. Access to this file permits the user to perform any type of analysis orgraphing of the data. For example, the user can easily identify and analyze sample vectors thatresult in output values between certain percentiles.

• Navigation. The user’s own spreadsheet, database, or software program mustbe used to read the specified formatted data and to perform analyses. Thedatabase file name is the case base name with a .BUO extension. For example,if the case was saved in siteA.rad, then the database would be saved assiteA.BUO. The format of the file is Microsoft Access Version 2000.

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5 VERIFICATION OF THE RESRAD-BUILD COMPUTER CODE

As part of a quality assurance program, RESRAD-BUILD has undergone extensivereview, benchmarking, and verification. Many models used in the code have been benchmarkedagainst other codes. For example, the external dose models have been benchmarked against theMonte Carlo N-particle (MCNP) code (Briesmeister 1993), and the radon model used in theRESRAD-BUILD code has been compared with the radon model used in RESRAD (Yu et al.2001). Recently, the NRC compared the DandD code Version 1.0 with the RESRADVersion 5.61 and RESRAD-BUILD Version 1.5 codes (NRC 1999). This section summarizes themost recent verification results using RESRAD-BUILD Version 3.0 and Microsoft Excelspreadsheets (Kamboj et al. 2001). An independent verification of the RESRAD-BUILD modelsand parameters was also conducted (Tetra Tech NUS, Inc. 2003).

5.1 VERIFICATION PROCEDURE

The results generated by RESRAD-BUILD Version 3.0 were compared with thoseobtained with hand-held calculators and spreadsheets. The equations and reference data listed inthe appendixes of this manual for different pathways were used in the calculations. Forverification purposes, several radionuclides H-3, C-14, Na-22, Al-26, Cl-36, Mn-54, Co-60,Au-195, Ra-226, Ra-228, Th-228, and U-238 were chosen to effectively test all pathways andmodels. Tritium, Ra-226, and Th-228 were chosen to test the special models used for tritium andradon in the RESRAD-BUILD code. The other radionuclides were selected to represent aspectrum of radiation types and energies.

Verification of the RESRAD-BUILD code was conducted with an initial check of all theinput parameters for correctness. Verification of the calculations was performed external to theRESRAD-BUILD code with Microsoft Excel (Version 7) to verify all the major portions of thecode. The verification was conducted on a step-by-step basis and used different test cases astemplates, since all possible options could not be considered. The following types of calculationswere investigated: (1) source injection rate, (2) air concentration in the room, (3) air particulatedeposition, (4) radon pathway model, (5) tritium model for volume source, (6) external exposuremodel, (7) different pathway doses, and (8) time dependence of dose.

Except for a dose from the direct external exposure pathway, the dose to a receptor in aroom depends on the radionuclide concentration in the air of that room. The radionuclide airconcentration, in turn, depends on the source injection rate. Therefore, the source injection ratecalculations were verified first. Then the air concentrations in one-room and two-room modelswere verified. Since air deposition depends on the air concentration in the room, air depositionwas verified next. The special radon and tritium models in RESRAD-BUILD were then verified.The external exposure models in RESRAD-BUILD were independently benchmarked with theMCNP transport code (Briesmeister 1993). Finally, the total dose for a single receptor calculatedby RESRAD-BUILD was compared and verified with the total dose calculated by the Excelspreadsheets. The time-independent part of the code was tested first (instantaneous dose

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calculations at time zero, without integrating over one year or the exposure duration). Then thetime-integrated dose was verified.

The following parameters used in the RESRAD-BUILD code (Version 3.0) were checkedand verified for correctness against their original source documents: inhalation, ingestion, airsubmersion, and external DCFs; external exposure model parameters; and radionuclide half-livesand other decay data. Excel spreadsheets were prepared that calculated the different pathwaysaccording to the source receptor configuration. Three spreadsheets were used for all verificationruns. The first spreadsheet used all the RESRAD-BUILD default parameters; the second usedlower-bound values of the input parameters; and the third used all the upper bound values for theinput parameters. The lower and upper bound values of the parameters were taken from Yu et al.(2000). The verification was performed for these three data sets to cover wide variations in inputvalues. Two direct exposure models based on source geometry are used in the RESRAD-BUILDcode. The first model for area and volume sources is based on a semi-infinite slab source withcorrections for geometric factors (Kamboj et al. 1998). This exposure model uses the externalDCFs from Federal Guidance Report No. 12 (Eckerman and Ryman 1993). The methodologydescribed by Kamboj et al. (1998) for corrections due to finite size was extended to includedifferences due to the source material. The second model for point and line contamination is asimple dose integral method (see Appendix F). The results of the external exposure models(point and line sources and area and volume sources) were also benchmarked with those from theMCNP transport code. For this comparison, MCNP Version 4A was used.

5.2 RESULTS AND DISCUSSION

Detailed results and discussion of the verification exercises are presented in Kamboj et al.(2001). The verification results for different types of calculations are summarized here. Table 5.1compares pathway doses for different source types calculated by RESRAD-BUILD with thosecalculated by Excel spreadsheets. For this comparison, all RESRAD-BUILD default parametersexcept for external exposure pathways were used. For the direct external exposure pathwaycomparison, a receptor at a height of 1 m from the center of a large source was assumed. For thedeposited material exposure pathway, the deposition was assumed to be in a room with a largefloor area. For all pathways except the radon inhalation pathway (where the contaminant isRa-226), the contaminant was assumed to be Na-22 at unit concentration (volume source =1 Bq g-1, area source = 1 Bq m-2, line source = 1 Bq m-1, and point source = 1 Bq). Noinconsistencies between the code output and spreadsheet calculations were found for thefollowing pathways: submersion, direct inadvertent ingestion, inadvertent ingestion of depositedmaterials, and inhalation of airborne radioactive particulates. For inhalation of aerosol indoorradon progeny, good agreement, to within 0.1%, was obtained. For direct external exposure,good agreement, to within 2%, was obtained; for external exposure to deposited material,agreement within 3% was obtained.

Table 5.2 compares the RESRAD-BUILD calculated doses and MCNP simulated dosesfor four source types (point, line, area, and volume) and for Au-195, Mn-54, and Co-60 using all

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TABLE 5.1 Comparison of RESRAD-BUILD and Spreadsheet Pathway Doses (�Sv yr-1) forDifferent Source Typesa

SourceType

DirectExternal

Exposure ofDepositedMaterial Submersion

InadvertentIngestion Inhalation

RadonInhalation

RESRAD-BUILD Volume 1.77 × 103 2.21 × 10-8 1.57 × 10-6 2.47 × 10-5 6.28 × 10-6 6.13 × 102

Area 3.38 × 10-2 5.26 × 10-8 3.75 × 10-6 5.88 × 10-5 1.49 × 10-5 8.51 × 10-4

Line 3.15 × 10-3 5.26 × 10-8 3.75 × 10-6 5.88 × 10-5 1.49 × 10-5 8.51 × 10-4

Point 1.05 × 10-3 1.46 × 10-9 1.04 × 10-7 1.63 × 10-6 4.15 × 10-7 2.37 × 10-5

Spreadsheet Volume 1.78 × 103 2.17 × 10-8 1.57 × 10-6 2.47 × 10-5 6.28 × 10-6 6.13 × 102

Area 3.32 × 10-2 5.16 × 10-8 3.73 × 10-6 5.88 × 10-5 1.49 × 10-5 8.50 × 10-4

Line NA 5.16 × 10-8 3.73 × 10-6 5.88 × 10-5 1.49 × 10-5 8.50 × 10-4

Point NA 1.43 × 10-9 1.04 × 10-7 1.63 × 10-6 4.15 × 10-7 2.36 × 10-5

a The doses for all pathways are the instantaneous doses for unit concentration (volumesource = 1 Bq g-1, area source = 1 Bq m-2, line source = 1 Bq m-1, and point source = 1 Bq) ofNa-22 except for the radon inhalation pathway, which is for Ra-226 contamination. The directexternal exposure pathway dose was compared only for volume and area sources; however, allsource type doses were benchmarked with the MCNP code. The comparison was performedwith all RESRAD-BUILD default parameters, except for exposure from direct external anddeposited material, where the receptor is at a height of 1 m from an infinitely large source area.

TABLE 5.2 Comparison of RESRAD-BUILDa and MCNP Dose Values (�Sv yr-1) for the DirectExternal Exposure Pathway

Point Line Area Volume

RadionuclideRESRAD-

BUILD MCNPRESRAD-

BUILD MCNPRESRAD-

BUILD MCNPRESRAD-

BUILD MCNP

Au-195 1.31 × 10-5 1.30 × 10-5 7.96 × 10-5 8.38 × 10-5 3.08 × 10-4 2.92 × 10-4 1.47 × 101 1.61 × 101

Mn-54 1.33 × 10-4 1.33 × 10-4 8.29 × 10-4 8.38 × 10-4 2.90 × 10-3 2.97 × 10-3 4.36 × 102 4.32 × 102

Co-60 3.76 × 10-4 3.76 × 10-4 2.36 × 10-3 2.36 × 10-3 8.27 × 10-3 8.38 × 10-3 1.33 × 103 1.32 × 103

a The doses were compared for unit concentration (volume source = 1 Bq g-1, area source = 1 Bq m-2, line source =1 Bq m-1, and point source = 1 Bq) of source with all RESRAD-BUILD default parameters.

5-4

RESRAD-BUILD default parameters to cover a wide energy range. For point sources, goodagreement, to within 1%, was obtained; for line, area, and volume sources, agreement within 5%was obtained. The verification results for different types of calculations are discussed below.

Input parameter check. The parameters checked included inhalation, ingestion, airsubmersion, and external DCFs; external exposure model parameters; and radionuclide half-livesand other decay data.

Source injection rate. Excellent agreement was obtained between the RESRAD-BUILDgenerated results and spreadsheet calculations.

Air concentration in the room. Air concentrations for four source types were comparedfor one- and two-room air quality models. Excellent agreement was obtained between theRESRAD-BUILD and spreadsheet calculations.

Air particulate deposition. Air particulate deposition was computed because it is used intwo pathways: external exposure due to deposited material and inadvertent ingestion directlyfrom the deposited materials.

Radon pathway model. The radon injection rate and the radon progeny concentrationcalculations were checked. For the point, line, and area sources, no difference was found in theRESRAD-BUILD and spreadsheet calculations of the source injection rates. However, thevolume source injection rates for Rn-222 and Rn-220 were different in two cases. The differencewas due to the density used in the calculations. For the spreadsheet calculations, it was assumedthat the particle density is input; in RESRAD-BUILD, the source bulk density was assumed. Ifthe same density values are used in RESRAD-BUILD, the results are the same (within round-offerrors) as the spreadsheet calculations. No significant differences in the RESRAD-BUILD andspreadsheet calculations were observed in radon progeny concentrations.

Tritium model for volume source. The tritium-transport model used in RESRAD-BUILDfor a volume source estimates the injection rate of tritiated water molecules into the indoor airfrom evaporation. This injection rate is then added to the source injection from erosion tocalculate the total source injection. This summed source injection rate is then used to calculateair concentration, air deposition, etc. No inconsistencies between the code output andspreadsheet calculations occurred for the injection rate of tritiated water molecules.

External exposure model. In the RESRAD-BUILD code, two direct exposure modelsbased on the source geometry are used. The first model for area and volume sources is based ona semi-infinite slab source with corrections for geometric factors. The second model for pointand line contamination is a simple dose integral method. The results of the external models werecompared with those from the MCNP transport code. The comparisons were performed atdifferent source-receptor configurations for Co-60, Mn-54, and Au-195. Good agreement (within5%) was observed.

Different pathway doses. The different pathway doses calculated by the RESRAD-BUILD code were compared with the spreadsheet calculations. No inconsistencies between the

5-5

code output and spreadsheet calculations were obtained for submersion, direct inadvertentingestion, inadvertent ingestion of deposited materials, inhalation of airborne radioactiveparticulates, and tritium volume source. For inhalation of aerosol indoor radon progeny, goodagreement, to within 1%, was obtained. For direct external exposure, good agreement to within2%, was obtained, and for external exposure to deposited material, agreement within 5% wasobserved. For the total receptor dose, there was no difference between the spreadsheet and coderesults.

Time dependence in dose calculations. No significant differences in the time-integratedand the average individual pathway dose (obtained by averaging the dose over different timeintervals) were obtained.

5-6

6-1

6 REFERENCES

Beyeler, W.E., et al., 1999, Residual Radioactive Contamination from Decommissioning;Parameter Analysis, NUREG/CR-5512, Vol. 3, Nuclear Regulatory Commission, Office ofNuclear Regulatory Research, Washington, D.C., Oct.

Biwer, B.M., et al., 2002, Technical Basis for Calculating Radiation Doses for the BuildingOccupancy Scenario Using the Probabilistic RESRAD-BUILD 3.0 Code, NUREG/CR-6755,ANL/EAD/TM/02-1, prepared by Argonne National Laboratory, Argonne, Ill., for Division ofSystems Analysis and Regulatory Effectiveness, Office of Nuclear Regulatory Research,U.S. Nuclear Regulatory Commission, Washington, D.C.

Briesmeister, J.F. (editor), 1993, MCNP A General Monte Carlo N-Particle Transport Code,Version 4A, LA-12625, Los Alamos National Laboratory, Los Alamos, N.M.

Cheng, J.-J., et al., 2000, RESRAD-RECYCLE: A Computer Model for Analyzing theRadiological Doses and Risks Resulting from the Recycling of Radioactive Scrap Metal and theReuse of Surface-Contaminated Material and Equipment, ANL/EAD-3, Argonne NationalLaboratory, Argonne, Ill., Nov.

Eckerman, K.F., and J.C. Ryman, 1993, External Exposure to Radionuclides in Air, Water, andSoil, Exposure to Dose Coefficients for General Application, based on the 1987 FederalRadiation Protection Guidance, EPA 402-R-93-081, Federal Guidance Report No. 12, preparedby Oak Ridge National Laboratory, Oak Ridge, Tenn., for U.S. Environmental ProtectionAgency, Office of Radiation and Indoor Air, Washington, D.C.

Eckerman, K.F., et al., 1988, Limiting Values of Radionuclide Intake and Air Concentration andDose Conversion Factors for Inhalation, Submersion, and Ingestion, Federal Guidance ReportNo. 11, prepared by Oak Ridge National Laboratory, Oak Ridge, Tenn., for U.S. EnvironmentalProtection Agency, Office of Radiation Programs, Washington, D.C.

Iman, R.L., et al., 1985, A FORTRAN 77 Program and User’s Guide for the Calculation ofPartial Correlation and Standard Regression Coefficients, NUREG/CR-4122,SAND85-0044 RG, prepared by Sandia National Laboratories, Albuquerque, N.M., forU.S. Nuclear Regulatory Commission, Washington, D.C., June.

Kamboj, S., et al., 1998, External Exposure Model Used in the RESRAD Code for VariousGeometries of Contaminated Soil, ANL/EAD/TM-84, Argonne National Laboratory,Argonne, Ill.

Kamboj, S., et al., 2000, Probabilistic Dose Analysis Using Parameter Distributions Developedfor RESRAD and RESRAD-BUILD Codes, NUREG/CR-6676, ANL/EAD/TM-89, prepared byArgonne National Laboratory, Argonne, Ill., for Division of Risk Analysis and Applications,Office of Nuclear Regulatory Research, U.S. Nuclear Regulatory Commission,Washington, D.C., May.

6-2

Kamboj, S., et al., 2001, RESRAD-BUILD Verification, ANL/EAD/TM-115, Argonne NationalLaboratory, Argonne, Ill., Oct.

Kennedy, W.E., Jr., and D.L. Strenge, 1992, Residual Radioactive Contamination fromDecommissioning, Technical Basis for Translating Contamination Levels to Annual TotalEffective Dose Equivalent, Vol. 1, NUREG/CR-5512, PNL-7994, prepared by Pacific NorthwestLaboratory, Richland, Wash., for U.S. Nuclear Regulatory Commission, Washington, D.C., Oct.

Tetra Tech NUS, Inc., 2003, Verification of RESRAD-BUILD Computer Code, Version 3.1,prepared for Argonne National Laboratory under Contract No. 1F-00741.

U.S. Atomic Energy Commission, 1974, “Termination of Operating Licenses for NuclearReactors,” Regulatory Guide 1.86, June.

U.S. Department of Energy, 1990, “Radiation Protection of the Public and the Environment,”DOE Order 5400.5, U.S. Department of Energy, Feb.

U.S. Environmental Protection Agency, 1997, Exposure Factor Handbook, EPA/600/P-95/002Fa, Office of Research and Development, National Center for EnvironmentalAssessment, Washington, D.C.

Wernig, M.A., et al., 1999, Residual Radioactive Contamination from Decommissioning: User’sManual, NUREG/CR-5512, Vol. 2, Nuclear Regulatory Commission, Office of NuclearRegulatory Research, Washington, D.C., May.

Yu, C., et al., 1993, Manual for Implementing Residual Radioactive Material Guidelines UsingRESRAD, Version 5.0, ANL/EAD/LD-2, Argonne National Laboratory, Argonne, Ill., Sept.

Yu, C., et al., 1994, RESRAD-BUILD: A Computer Model for Analyzing the Radiological DoseResulting from the Remediation and Occupancy of Buildings Contaminated with RadioactiveMaterial, ANL/EAD/LD-3, Argonne National Laboratory, Argonne, Ill.

Yu, C., et al., 2000, Development of Probabilistic RESRAD 6.0 and RESRAD BUILD 3.0Computer Codes, NUREG/CR-6697, ANL/EAD/TM-98, prepared by Argonne NationalLaboratory, Argonne, Ill., for Division of Risk Analysis and Applications, Office of NuclearRegulatory Research, U.S. Nuclear Regulatory Commission, Washington, D.C., Nov.

Yu, C., et al., 2001, User’s Manual for RESRAD Version 6, ANL/EAD-4, Argonne NationalLaboratory, Argonne, Ill., Sept.

A-1

APPENDIX A:

INDOOR AIR QUALITY MODEL

A-2

A-3

APPENDIX A:

INDOOR AIR QUALITY MODEL

An indoor air quality model has been developed to simulate the transport of radiologicalcontaminants inside a building with air exchange between compartments and with outdoor air.The air quality model assumes that particulates in the indoor air of any compartment are wellmixed; therefore, the pollutant concentration is the same for every point in the air within thecompartment. The air exchange and ventilation of building compartments are discussed inSection A.1; the models used to calculate the radionuclide concentrations in the indoor air arepresented in Section A.2. The adaptation of the air quality model to calculate airborneconcentrations of radionuclides, including radon and its progeny, is presented in Section A.3.

A.1 BUILDING VENTILATION AND INFILTRATION

Consider a three-compartment building represented by the schematic configurationshown in Figure A.1. From the principle of conservation of mass, applied at any buildingcompartment i and assuming a steady-state condition, we can write the following generalexpression:

,Q = Q ji

i)(j

j=ij

i)(j

j= ∑∑≠≠

30

30 (A.1)

where

Qij = flow from compartment i to compartment j (m3/h) and

i or j = compartment index, representing the outdoor air and the first, second,and third compartment for i = 0, 1, 2, and 3, respectively.

The net inflow rate, Nij, from compartment i to compartment j is defined as:

. QQ = N jiijij − (A.2)

The value of Nij can be negative, meaning that the net air flow is from compartment j intocompartment i.

Now, applying Equation A.1 to compartment number 1 (i = 1) yields:

. Q + Q + Q = Q + Q + Q 312101131210 (A.3)

A-4

FIGURE A.1 Schematic Representation of the Three-Compartment Building, Showingthe Inflow and Outflow of Air in Each Compartment

The RESRAD-BUILD model assumes that compartment 1 is not adjacent to compartment 3 andthus does not communicate directly with compartment 3. Therefore, the following expressionapplies:

. = Q = Q 03113 (A.4)

Equations A.3 and A.4 yield:

Q + Q = Q + Q 21011210 , (A.5)

that is, the total inflow of air to compartment 1 is equal to the total outflow of air fromcompartment 1.

Similarly, applying Equation A.1 to compartment 2 (i = 2) yields:

. Q + Q + Q = Q + Q + Q 321202232120 (A.6)

Finally, applying Equation A.1 to compartment 3 (i = 3) and considering Equation A.4,yields:

. Q + Q = Q + Q 23033230 (A.7)

Note that summing Equations A.5, A.6, and A.7 yields:

,Q + Q + Q = Q + Q + Q 030201302010 (A.8)

A-5

which expresses the fact that the total outflow of air from inside the building is equal to the totalinflow of air from outside.

The ventilation (or air exchange) rate of a building (or a compartment) is defined as thenumber of total volumes of air contained in the building (or the compartment) that is beingexchanged with outside air (or air from other compartments) per unit of time. For example, abuilding with a ventilation rate of 1 h-1 has its volume of air replaced once each hour. The airexchange rate a

iλ for compartment i can be calculated as:

,V

Q

= V

Q

= i

ij

i)(j

j=

i

ji

i)(j

j=

ai

∑∑≠≠

30

30

λ (A.9)

where Vi is the volume of compartment i.

The building air exchange rate abλ is:

.3

1

03

13

1

03

1 V

Q =

V

Q

ii

ii

ii

iiab ∑

∑∑∑

=

=

=

== (A.10)

The measurement methodology and ranges of air exchange rate are discussed by Yu et al. (1993;2000) and Nero (1988). A detailed discussion on the air exchange rate for different buildingtypes (commercial and residential) and their distributions is given in Appendix J.

A.2 INDOOR AIR CONCENTRATION

Assuming that the pollutant in the indoor air is well mixed within a generic compartmenti, the mass balance of a pollutant within the volume Vi, due to the contribution of one specificsource, can be expressed as:

( ) ,tStI + QtCtCQ + tCV = dt

tCdV n

iniij

i)(j

j=ni

njji

i)(j

j=niirn

ni

i )()()()()()( 3

03

01 −∑−∑

≠≠

−λ (A.11)

where

i = compartment index (i = 0, 1, 2, and 3) representing, respectively, theoutdoor air (0th compartment) and the first, second, and thirdcompartments;

= concentration at time t of a radionuclide of order n in its radioactivedecay series, present in the air of compartment i (pCi/m3);

rn = radioactive decay constant of radionuclide n;

)t(Cni

A-6

Qij = flow of air from compartment i to compartment j (i � j) (m3/h);

)t(I ni = injection rate of radionuclide n into the air of compartment i at time t

(pCi/h);

Vi = volume of compartment i (i = 1, 2, and 3) (m3); and

)(tS ni = sink term for radionuclide n in compartment i at time t (pCi/h).

Each term of Equation A.11 represents the variation in time of a part of the mass of thematerial within the volume Vi due to some specific process. The term at the left side of theequation represents the net change (accumulation or depletion) of the pollutant within volume Viper unit of time. The first term on the right-hand side of the equation represents the generation ofthe principal radionuclide of order n due to the radioactive decay of its predecessor of order(n-1). The second term on the right side represents the total contribution due to the inflow of airfrom the neighbor compartments. The third term represents the loss of material in compartment idue to the total outflow of air into the neighbor compartments. The sink term )(tS n

i represents the

loss of mass of airborne material due to radioactive decay, ,nriS and deposition, ,n

diS and can be

expressed as:

,tS + tS = tS ndi

nri

ni )()()( (A.12)

where

)()( t CV = tS niirn

nri λ , (A.13)

tCV = tS niidi

ndi )()( λ , (A.14)

di = V i

Ai ud

, (A.15)

rn = radioactive decay constant of radionuclide n (h-1),

di = deposition rate (h-1),

ud = deposition velocity (m/h), and

Ai = horizontal area of compartment i (m2).

Therefore, from Equations A.12, A.13, and A.14, the sink term ,niS can be expressed as:

( ) .t CV + = tS niidirn

ni )()( λλ (A.16)

A-7

The term )(tI ni in Equation A.11 represents the total injection of material

(radionuclide n) into the air of compartment i due to the source present within the compartment,,n

SiI and due to resuspension of the material deposited on the floor, .nRiI It can be expressed as:

,tI + tI =t I nRi

nSi

ni )()()( (A.17)

where )(tI nSi is the source-dependent term representing the direct injection rate of radioactive

material into the indoor air. It depends on the mechanical removal or erosion rate of the source(or on the radon/HTO diffusion process, for the case of radon source or tritium volume source)and must be evaluated specifically for each defined source and operational scenario. Theresuspension term, ),(tI n

Ri depends on the resuspension rate, R, and the deposition velocity, ud,and can be expressed as (see Appendix B):

,)t(C ni

R + rn

Ai u d R = )t(I nRi

λλλ (A.18)

,)t(C ni V i

V i

Ai u d R + rn

R =)t(I nRi

λλλ (A.19)

or

. )t(C ni V i

R + rn

di R = )t(I nRi

λλλλ (A.20)

Therefore, from Equations A.17 and A.20, the injection rate niI can be expressed as:

. )t(C ni V i

R + rn

di R + )t(I nSi = )t(I n

i

λλλλ (A.21)

Substituting Equations A.16 and A.21 into Equation A.11 yields the following general massbalance equation:

( ) tI + QtCtCQ + tCV = dt

tCdV n

Siij3

ij

j=ni

njji

3

ij

j=)(n

iirn

ni

i )()()()()(

001 ∑−∑

≠≠

−λ

( ) . )t(C niV idi + rn)t(C n

i V i R + rn

di R + λλ−

λλλλ (A.22)

A-8

Now, substituting the steady-state compartment mass balance Equation A.1 into A.22 andassuming steady-state conditions, Equation A.22 becomes (for each compartment i):

( ) )t(I + Q )t(C )t(CQ + )t(CV nSiji

ij

=jni

njji

ij

=j)(n

iirn ∑−∑λ≠≠

− 30

30

1

( ) , = )t(C niV idi + rn)t(Cn

i V i R + rn

di R + 0λλ−

λλλλ (A.23)

( ) )t(CQ)t(C Q + V +

+ n

jji

ij

=jniji

ij

=jiRrn

diRdirn ∑−

∑

λλλλ−λλ

≠≠

30

30

. )t(C V + )t(I = )n(iirn

nSi

1−λ (A.24)

Applying Equation A.24 to all three internal compartments of the building (i = 1, 2, 3) generatesa system of three equations related to the three unknowns, ,1

nC ,2nC and ,3

nC which can thenbe solved.

So, applying Equation A.24 for compartments 1, 2, and 3 yields, respectively:

)()()( 331221113

1

011

1 tCQtCQtC Q + V +

+ nnn

j

j

j=Rrn

dRdrn −−

∑

−

≠

;1110011 )t(CV + )t(CQ + )t(I = )(n

rnnn

S− (A.25)

)t(CQ)t(C Q + V +

+ (t) + CQ nn

j

j

j=Rrn

dRdrn

n33222

3

2

022

2112 −

∑

−−

≠

; )t(CV + )t(CQ + )t(I = 1)(n22rn

n002

n2S

−λ (A.26)

)t(C Q + V +

+ + )t(CQ)t(CQ n

33j3

3j

0=j3Rrn

dRdrn

nn

∑

λλλλ−λλ−−

≠

33223113

. )t(CV + )t(CQ + )t(I = 1)(n-33rn

n003

n3S λ (A.27)

Using a matrix notation, the system of equations represented by Equations A.25, A.26, and A.27can be rewritten as:

A-9

A × x = b , (A.28)

where A is a systematic coefficient matrix of order 3 that can be written as:

QV

Q

Q

Q

QV

Q

Q

Q

QV

= A

j

j

j=Rrn

dRdrn

j

j

j=Rrn

dRdrn

j

j

j=Rrn

dRdrn

∑+

λ+λ

λλ−λ+λ

−

−

−

∑+

λ+λ

λλ−λ+λ

−

−

−

∑+

λ+λ

λλ−λ+λ

≠

≠

≠

33

3

033

3

31

23

23

2

022

2

21

13

12

13

1

011

1

32

(A.29)

The vectors of the unknown variables and the independent terms, x and b, are writtenrespectively as:

.

)t(CV)t(CQ)t(I

)t(CV)t(CQ)t(I

)t(CV)t(CQ)t(I

=

)t(C

)t(C

)t(C

=

)n(rn

nns

)n(rn

nns

)n(rn

nns

n

n

n

λ++

λ++

λ++

−

−

−

1330033

1220022

1110011

3

2

1

b;x (A.30)

Equation A.28 is a general expression representing the air quality model. It can be solvedfor the concentrations ),(1 tC n ),(2 tC n and )(3 tC n of a radionuclide n. Compartments 1 and 3 areassumed to be separated, and no air flows between them. Therefore, Q13 = Q31 = 0. In the currentversion of RESRAD-BUILD, the outdoor air concentration )(0 tC n is assumed to be zero.

A.3 ADAPTATION OF THE AIR QUALITY MODEL

This air quality model can be used to calculate the airborne concentration of aradionuclide of order n at time t in its radioactive decay series or the concentration of radon andits decay progeny in the air of compartments 1, 2, and 3. Use of the model to simulate these caseswould require the following adaptation.

Case 1 � Airborne concentration of a radionuclide of order n:

• The injection rate )(tI nSi is evaluated according to the behavior of the source,

such as source erosion rate (see Appendix D).

• The concentration )t(C )n(i

1− is given by the concentration of the predecessor

radionuclide in the series. If n = 1, then )t(C )n(i

1− is made equal to zero.

A-10

Case 2 � Airborne radon concentration:

• The rate of radon injection, ),(tI nSi from the source into the indoor air of

compartment i is evaluated by solving the radon transport equation within thesource (see Appendix C).

• The order number n is made equal to 1.

• The precursor concentration )t(Ci0 is equal to the concentration of

radium-226 (for the case of radon-222) or thorium-228 (for the case ofradon-220) in the air of compartment i, due to a direct release from the source.

)(0 tCi , which will be used for the radon calculations, can be calculated

according to Case 1.

• In most cases, the radon calculations could be performed by neglecting thecontribution from the indoor air precursor concentration )(0 tCi .

• �� di = 0.

Case 3 � Airborne concentration of radon progeny:

• The order number n is made equal to 2, 3, and 4.

• )()(1 tCtC Rnii = for each i. Note that )(1 tCi is calculated according to Case 2.

• The concentration of the radon progeny is determined by solvingEquation A.28 sequentially with n = 2, 3, and 4.

• The injection rate is 0)( =tI nSi for all i and n.

• Specific details are shown in Appendix C.

Case 4 � Airborne concentration of tritium:

• For point, line, or area sources, the injection rate, )(tI nSi , is calculated by using

the “removable fraction” parameter that describes the behavior of the sourcematerial.

• For volume source, the injection rate, )(tI nSi , is calculated by considering two

mechanisms: the erosion mechanism and the vaporization/diffusionmechanism. Specific discussions on the erosion and the vaporization/diffusionmechanism are provided in Appendixes D and G, respectively.

• The concentration of Ci(n–1) (t) is zero since there is no precursor for tritium.

A-11

A.4 REFERENCES

Nero, A.V., 1988, “Radon and Its Decay Products in Indoor Air: An Overview,” in Radon andIts Decay Products in Indoor Air, W.W. Nazaroff and A.V. Nero (editors), John Wiley & Sons,New York, N.Y.

Yu, C., et al., 1993, Data Collection Handbook to Support Modeling the Impacts of RadioactiveMaterial in Soil, ANL/EAIS-8, Argonne National Laboratory, Argonne, Ill., April.

Yu, C., et al., 2000, Development of Probabilistic RESRAD 6.0 and RESRAD BUILD 3.0Computer Codes, NUREG/CR-6697, ANL/EAD/TM-98, prepared by Argonne NationalLaboratory, Argonne, Ill., for Division of Risk Analysis and Applications, Office of NuclearRegulatory Research, U.S. Nuclear Regulatory Commission, Washington, D.C., Nov.

A-12

B-1

APPENDIX B:

AIR PARTICULATE DEPOSITION

B-2

B-3

APPENDIX B:

AIR PARTICULATE DEPOSITION

The objective of the deposition model is to evaluate the surface concentration, ),(tC ndi of

the principal radionuclide of order n in the decay series, at each compartment i of the building, asa function of the respective airborne concentration in the indoor air of compartment i. For thederivation of the deposition model, consider the schematic representation of a genericcompartment i, as shown in Figure B.1.

Thus, from a mass balance principle applied to the projected plane surface ofcompartment i, the following expression can be derived:

,tC A tC A tC A u = dt

tCdA n

diiRndiirn

niid

ndi

i )()()()( −− (B.1)

where

)(tC ndi = surface concentration at time t of principal radionuclide of order n in

the radioactive decay series, due to deposition at the projectedhorizontal surface of compartment i (pCi/m2);

)(tC ni = airborne concentration at time t of radionuclide n, in the indoor air of

compartment i (pCi/m3);

ud = average deposition velocity of the airborne radioactive dust particulates(m/h);

rn = radioactive decay constant of radionuclide n (1/h);

R = resuspension rate of deposited dust particulates into the air, or thefraction of the deposited dust particulates that is resuspended into theindoor air per unit of time (1/h); and

Ai = surface area of the floor of compartment i (m2).

Each term in Equation B.1 represents the variation of mass (activity) on the projectedplane surface, per unit of time, due to different processes. The term on the left-hand siderepresents the total accumulation/depletion of mass (activity) on the surface. The first term onthe right-hand side represents the addition of mass due to the deposition of dust particulates. Thesecond term represents the loss of mass due to radioactive decay. Finally, the third termrepresents the loss of mass due to the resuspension of deposited dust particulates back into theindoor air.

B-4

FIGURE B.1 Schematic Representation of a Compartment i of theBuilding, Showing the Deposition of Dust Particulates onto the ProjectedHorizontal Surface

Assuming a steady-state condition, the mass balance Equation B.1 yields:

,(t) = C(t)C(t)C u ndiR

ndirn

nid 0−− (B.2)

or

. )t(C ni

R + rn

u d = )t(C ndi

(B.3)

Equation B.3 is used to calculate ),(tC ndi at each compartment i, as a function of the

respective airborne concentration ).(tC ni The contribution for the total injection rate at each

compartment i due to resuspension can be evaluated from the last term of Equation B.1. That is:

,tC A = tI ndiiR

nRi )()( (B.4)

B-5

where nRiI is the rate of injection of radionuclide n into the indoor air of compartment i due to

resuspension of deposited dust particulates (pCi/h). Substituting Equation B.3 into B.4 yields:

. )t(C ni

R + rn

Ai ud R = )t(I nRi

(B.5)

Equation B.5 is used in the air quality model (see Appendix A) to represent thecomponent of the injection rate due to resuspension.

B-6

C-1

APPENDIX C:

RADON AND ITS PROGENY CONCENTRATION

C-2

C-3

APPENDIX C:

RADON AND ITS PROGENY CONCENTRATION

C.1 RADON FLUX

The airborne radon concentration in the indoor air of compartment i is calculated byusing the generic air quality model, as described in Appendix A. However, to apply the airquality model, it is necessary to evaluate the radon injection rate )(tI Rn

Si directly from the source

into the indoor air of compartment i. The rate of radon injection into the indoor air depends onthe concentration of the radon parent within the source and on the geometric and physicalproperties of the source. Therefore, )(tI Rn

Si is defined for each type of source: surface, line, point,

and volume. For surface, line, and point sources, )(tI RnSi (pCi/s) at time t is calculated as:

,tA F = tI ptotal

RnRnSi )()( (C.1)

where

FRn = fraction of radon generated within the source that escapes from thesource and is injected into the air (dimensionless),

= radon decay constant (s-1), and

)(tA ptotal = total amount of the radon parent radionuclide present within the

source at time t (pCi).

For a volume source, the radon injection rate, )(tI RnSi , is evaluated differently, according

to the following:

,tJA = tI sRnSi )()( (C.2)

where

As = surface area of the face of the volume source that is exposed to the indoorair of compartment i (m2) and

J(t) = flux density of radon activity (or radon flux, for short) through theexposed face of the volume source [pCi/(m2 × s)] at time t.

The variables FRn and )(tA ptotal are given as input parameters to the model. Therefore, the

calculation of )(tI RnSi for surface, line, and point sources is a straightforward procedure, based

directly on Equation C.1. Yet, for volume sources, the radon flux is not given as an input

C-4

parameter and must be evaluated specifically for each case. Sections C.1.1 to C.1.3 describe themodel for calculating the radon flux J(t) for the cases in which the volume sources are defined.

C.1.1 Mathematical Model

Consider an initial three-dimensional configuration of a volume source composed of upto five distinct regions, as shown in Figure C.1. The present conceptual model assumes thatbecause of geometric considerations, the total flow of radon activity from the lateral (smaller)faces of the volume source is negligible compared with the total flow through the larger facesthat are exposed to the indoor air. This assumption implies that, if the lateral flux is neglected,the distribution of radon concentration in the lateral (boundary) zones within the source could beassumed invariable. Neglecting the value of Jlat increases the calculated values of Ji and Jj,resulting in a conservative estimation of indoor radon concentration. Under these assumptions,the three-dimensional configuration in Figure C.1 can be further simplified and represented by afive-zone, one-dimensional configuration, as shown in Figure C.2.

The general mass balance equation for radon activity in a two-phase porous systemcomposed of solid phase and gas phase (no moisture content) in any region represented inFigure C.2 can be expressed as:

,nS + nR J= t

(nC) −×∇−∂

∂ ��(C.3)

where

C = radon activity concentration in the pore space (pCi/m3),

J = bulk flux density of radon activity through the matrix (pCi � m-2 � s-1),

R = radon sink term (pCi � m-3 � s-1),

S = radon source term (pCi � m-3 � s-1), and

n = total (volumetric) porosity.

Each term of Equation C.3 expresses the variation of radon activity per unit of total volume andper time. These terms are functions of time and/or space. For simplicity in expression, the timeand space dependency is omitted in the notation.

In the absence of convective flow of the gaseous phase in the porous medium, the bulkflux density of radon activity, J, can be expressed by the Fickian diffusion equation:

,CnD = J e ∇−�

(C.4)

C-5

L1

0

L2

L3

L4

L5

x

J lateral

Ji

Region 1

Region 2

Region 3

Region 4

Region 5

Jj

CYA10107

FIGURE C.1 Three-Dimensional Schematic Representation of a Volume Source(showing its five distinct regions and the radon flux densities at the surfaces ofthe source)

L10 L

2L

3L

4L

5

x

Jj 1 2 3 4 5

Regions

Ji

CYA10108

FIGURE C.2 One-Dimensional Schematic Representation of a Volume Source (showingits five distinct regions and radon flux densities at the surfaces of the source)

C-6

where De is the effective diffusion coefficient of radon in the porous medium (m2��-1).

The source of radon activity into the pore volume of the porous medium can be evaluatedby the following expression:

,n

npCsS

−λρε=1

(C.5)

where

ε = radon emanating factor,

s = density of solid phase of the porous medium (kg/m3),

Cp = concentration of the radon parent radionuclide in the solid phase (pCi/kg),

= radon decay constant (1/s), and

n = total porosity of the medium.

The decay of radon activity (the sink term) in the pore volume can be expressed as:

. C = R λ (C.6)

Now, considering the steady-state condition in the one-dimensional configuration and theconstitutive expressions above, the general mass balance equation for radon becomes:

,nS = Cn + dx

dCnDedx

d λ

− (C.7a)

,nS = Cn + dx

CdnDe λ

2

2

− (C.7b)

or

, S= C + dx

CdDe λ

2

2

− (C.7c)

where the porosity n and the diffusion coefficient De are assumed invariable with distance.

Equation C.7a is a nonhomogeneous, linear (constant coefficients), second-order,ordinary differential equation representing the transport of radon activity in a one-dimensional

C-7

porous medium configuration. The general solution for the nonhomogeneous transport equationabove can be expressed as:

,S

+ eK + eK = C rxrx

λ−

21 (C.8a)

or

,S

+eKeK = C DD L

x

L

x

λ

−+ 21 (C.8b)

where K1 and K2 are linear coefficients to be determined from the boundary conditions,and r represents the inverse of the diffusion length, LD, and is given by:

, = l

DL = r

eD

(C.9)

where LD is the diffusion length (m).

Equation C.8 represents the profile of radon activity concentration, C, within a specificone-dimensional region where all the parameters (such as De�� S, s, and n) are assumed to beconstant and where the coefficients K1 and K2 are calculated on the basis of the boundaryconditions imposed on the defined region of the domain. Equation C.8 can also be used torepresent the profile of C in a multiple-region, one-dimensional configuration, if each definedregion has constant and homogeneous properties. In this case, the constants Ki1 and Ki2, for eachregion i, must be evaluated on the basis of the boundary conditions imposed on the externalboundaries of the domain and on each interface between two defined regions.

C.1.2 General Boundary Conditions

Two types of physical boundaries need to be considered in solving a problem of radondiffusion in a one-dimensional porous medium configuration: (1) at the interface between theporous medium and open air (either outdoor atmosphere or indoor air) and (2) at the interfacebetween two defined porous medium regions of the domain.

Different boundary conditions are imposed at these boundaries. Thus, at theopen-air/porous-medium interface, the radon activity concentration is assumed to besubstantially smaller than the values of C inside the medium, where the radon source is present.Therefore, as an approximation, the value of C = 0 is assumed at this boundary. That means, atvalues of x = 0 and x = L5, this boundary condition would be expressed as follows:

0 = C =0)(x (C.10a)

and. = C )L=(x 5

0 (C.10b)

C-8

At the interfaces between two different regions in the porous medium domain, theprinciple of continuity is applied as a boundary condition. That means at an interface i, located ata generic point xi, the values of radon activity concentration, C, and the bulk flux density ofradon activity, J, should satisfy the following limit expressions:

C = C +)x=(x-)x=(x ii(C.11a)

and

. dx

dCnD =

dx

dCnD e

+)x=(xe

)x=(x ii

−(C.11b)

C.1.3 Analytical Solution: General Multilayer Configuration

The general solution for the one-dimensional radon diffusion equation, Equation C.8, canbe applied to represent the profile of radon activity concentration and flux density along amultiregion, one-dimensional configuration representing the source within the wall.

To simplify the equations, a three-layer source will be considered as an example here.Thus, consider a one-dimensional physical configuration of three porous layers, with thicknessesl1, l2, and l3 and homogeneous properties within each layer. Also, assume the system ofcoordinates at the origin of the configuration. The boundaries of the system will be located at thedistances x = 0, L1, L2, and L3. Applying Equation C.8 into this configuration results in thefollowing system of equations:

,L x ,S + eK + eK = xC xrxr11

11211 0)( 1 ≤≤−

λ(C.12a)

,L x L ,S + eK + eK = xC xrxr21

22221

22)( ≤≤−

λ(C.12b)

. L x L ,S + eK + eK = xC xrxr32

33231

33)( ≤≤−

λ(C.12c)

This set of equations involves six (2n = 6) unknown parameters Kij, where i = 1, 2, 3 andj = 1, 2. The values of these parameters specify a defined physical system. A three-layerconfiguration has two (n – 1 = 2) internal boundaries, which, from the boundary conditionsrepresented by Equation C.11, generate four (2n – 2 = 4) equations. The two external boundariesprovide the other two needed equations for solving the system. The conditions imposed on theseexternal boundaries can be represented by Equation C.10a or C.10b.

C-9

Thus, applying the condition represented by Equation C.10 on the first boundary of thesystem (at x = 0) yields:

. S= K + K λ1

1211 − (C.13a)

Then, applying the condition represented by Equation C.11 on an internal boundary betweenregion i and region (i + 1) at the distance (x = Li) of the system yields:

( ) ( ) ( ) ( ) ,S + Ke + Ke = S + Ke + Ke+i

)+(iLr

)+(iLri

iLr

iLr i+ii+iiiii

λλ1

21112111 −− (C.13b)

and

( ) ( )

( ) ( ) . KerDnKerDn

= KerDnKerDn

)+(iLr

+ie+i)+(iLr

1+ie+i

iLr

ieiiLr

iei

i+i

+i

i+i

+i

ii

i

ii

i

2111111

21

11

11

−

−

−

−(C.13c)

For the last boundary of the system, or the external boundary of the third layer, thecondition imposed there could be represented by the following expression:

( ) ( ) . S= Ke + Ke LrLr 33231

3333 −− (C.13d)

The system of equations represented by Equations C.13a through C.13d contains six(2n = 6) equations related to the six unknowns, Kij. It can be represented by the following matrixequation:

,b = kA × (C.14)

where A is a pentadiagonal coefficient matrix that can be written as:

.

ee

erDerDerDerD

eeee

erDerDerDerD

eeee

= A

LrLr

LrLrLrLr

LrLrLrLr

LrLrLrLr

LrLrLrLr

−−

−−

−−

−−

−

−−

−−

−−

−−

3333

23232222

23232222

12121111

12121111

0000

00

00

00

00

000011

33332222

22221111

(C.15a)

C-10

To save space in writing the matrix identity above, the product niDei was substituted by

the bulk diffusion coefficient Di. By definition, the product of porosity times the effective

diffusion coefficient is equal to the bulk diffusion coefficient. That is,

. D = Dn iei i(C.15b)

The vectors of the unknown variables and the independent terms k and b are written,respectively, as:

.

0

0 = and

3

23

12

1

32

31

22

21

12

11

−

−

−

−

λ

λ

λ

λ

S

SS

SS

S

b

K

K

K

K

K

K

= k (C.15c)

The solution of Equation C.14 provides the values of the coefficients Kij, which couldthen be used in Equation C.12 to represent the profile of radon activity concentration throughoutthe multilayer configuration.

The flux density of radon activity at both extremities of the system (at x = 0 and x = L3)could then be derived from Equations C.4 and C.12. Thus, at x = 0, the flux J (x = 0) is given by:

( ) eKr eKr Dn =

CDn = J

xrxr ,)=(xe

)=(xe)=(x

11121111 011

0110

−−−

∆−

or

( ) . KK r D n = J e)=(x 1211110 1−− (C.16)

C-11

Similarly, for X = L3, the flux density J(x = L3) is given by:

( ). eKeK r D n = J LrLre)L=(x

3333

3 3231333−−− (C.17)

Finally, after calculating Ji from Equations C.16 and C.17, the radon injection rate fromeach face of the volume source into the indoor air of the respective compartment i can becalculated from Equation C.2. This methodology is implemented in the RESRAD-BUILD codefor up to five regions of different material.

C.2 RADON PROGENY

The objective of the radon dosimetry model is to evaluate the effective dose equivalentdue to inhalation of the airborne radon progeny. The model presented here is an adaptation of theradon dosimetry model currently used in the RESRAD computer code (Yu et al. 2001).

Consider a three-compartment building as shown in Figure C.3. The terms shown in thefigure are defined as follows: Fout is the fraction of time spent outside the building(dimensionless); Fin is the fraction of time spent inside the building (dimensionless); Fi is thefraction of all the time spent inside the building in which the individual stays in the compartmenti (with i = 1, 2, 3 for the first, second, and third compartment, respectively) (dimensionless); n

iCis the indoor air concentration of radon decay products (n = 2, 3, 4) for either radon-222 orradon-220 progeny in the compartment i (i = 1, 2, 3) (pCi/m3); WLi is the working levelconcentration of radon decay products for either radon-222 or radon-220 progeny

i = 1

WLM1 F1WL1C1n

, , ,

i = 2

WLM2 F2WL2C2n

, , ,

i = 3

WLM3 F3WL3C3n

, , ,

Fin Fout

CYA10109

FIGURE C.3 Schematic Representation of the Three-Compartment Building

C-12

in the indoor air of compartment i (i = 1, 2, 3) (in units of WL); WLMi is the exposure to theindoor air concentration of radon decay products for either radon-222 or radon-220, in thecompartment i (i = 1, 2, 3) (in units of working level month [WLM]); and Rn

iD is the effective

dose equivalent due to the inhalation of radon decay products in the indoor air of compartment i(i = 1, 2, 3) (mrem/yr).

The algorithm to calculate the radon decay product dosimetry can be summarized in thefollowing four steps:

1. Calculate niC the indoor air concentration of radon and its decay products

(obtained by applying the air quality model, Appendix A).

2. Calculate the WLi, based on the values of niC .

3. Calculate the exposure (WLMi) to the radon decay products, based on the WLi

and the exposure time.

4. Calculate the effective dose equivalent RniD , based on the WLMi and the

related dose conversion factors (see Section C.5).

C.2.1 Airborne Radon Progeny Concentration

The calculation of the airborne concentration of the radon short-lived decay products inthe indoor air of compartment i is based on a variation of the model proposed by Jacobi (1972)and extended by Porstendörfer (1984) and Bruno (1983). Figure C.4 schematically represents themain interactions among the different stages of the radon decay products, as addressed in themodel. According to the adopted notation, the radon progeny is designated by the index n, wheren is equal to 1, 2, 3, and 4 for radon and its first, second, and third decay products, respectively.For convenience, the first, second, and third radon decay products are designated, in general, aselements A, B, and C, respectively. For example, in the case of the radon-222 family, the n indexwould represent radon-222, polonium-218, lead-214, and bismuth-214, for n equal to 1, 2, 3,and 4, respectively. In this case, polonium-218, lead-214, and bismuth-214 are described aselements A, B, and C, respectively. Similarly, for the case of the radon-220 family, the n indexwould represent radon-220, polonium-216, lead-212, and bismuth-212, respectively. Thesubscripts fr, at, and po designate, respectively, the free, attached, and plated-out states in whichthe radon decay products may exist.

The atom of element A is formed as a free ion as a result of the decay of a radon atom.Soon after being formed, the ions of element A join with other ions to form an ionized molecularcluster. The molecular cluster and the ions recently formed are usually considered together inwhat is designated as the “free state” (fr) of the decay product. This state is represented by thesecond block from the top, in the center of Figure C.4. At this free state, the atom of element A

C-13

FIGURE C.4 Schematic Representation of the Interrelationships among the Several Statesof the Short-Lived Radon Decay Products (The superscripts 1, 2, 3, and 4 represent radonand its first three decay products, respectively.)

may follow several possible courses: (1) attach to airborne particulates (one block at right inFigure C.4); (2) plate out to exposed surfaces, such as walls within the compartment (one blockat left); (3) decay to the free stage of element B (one block below, in Figure C.4); or (4) beventilated out of compartment i.

At the “attached state” (at), the atoms of element A are attached to the airborne dustparticulates and may have the following fate: (1) decay to element B and remain attached to thesurface of the airborne dust particulate; (2) decay to element B and be ejected out of the hostparticle, due to the recoil energy from the alpha-decay process; (3) deposit onto the floor surface,together with the deposition of the air particulates; or (4) be ventilated out of compartment i.

C-14

At the “plated-out state” (po), the atoms of element A are plated onto exposed surfaces inthe compartment and, consequently, are removed from the indoor air. However, the atoms ofelement B generated from the radioactive decay of element A in the plated-out location can bereintroduced, as a free state atom, into the indoor air due to the recoil energy from the alpha-decay process. 1

The atoms of element B are faced with almost the same destiny as described forelement A. Yet, because the recoil energy from beta-decay is not sufficient to promotedetachment, the atoms of element C formed from the decay of element B mostly remain attachedto their host.

The rate constant for the decay pathway of radon and its progeny is simply theradioactive decay constant, n, where n is equal to 1, 2, 3, and 4, representing radon and theelements A, B, and C, respectively. The rate constant for the decay of element A, either in theattached or plated-out state, followed by detachment and the generation of element B in a freestate, is equal to the decay constant, 2, multiplied by the appropriate probability that a free atomwill be created due to recoil. Pat and Ppo are the probabilities that a free atom of element B willbe created due to recoil and detachment from attached and plated-out atoms of element A,�� at. Itdepends mainly on the airborne particle concentration and size distribution (Bruno 1983).Similarly, the rate constant for the plate-out pathway is called the plate-out rate, po. It dependson the surface-to-volume ratio of the compartment and on the transport properties of the freeatoms within the air in the compartment. A list of the range of measured and reported values forthe constants discussed above, as reported by Bruno (1983), is presented in Table C.1. Thedefault vault used in the code for the attachment rate and plate-out rate is 0.03 s-1.

The airborne concentration of radon progeny will be calculated sequentially by applyingthe mass balance equation (as described in Appendix A) to find the radon concentration first and,then, to each unshaded block of Figure C.4 to find the concentration of the radon progeny at eachstate. Therefore, in relation to the radon progeny calculations, the air quality model will beapplied in eight consecutive steps to calculate (1) the radon concentration; (2) the concentrationsof element A in the free, attached, and plated-out states; (3) the concentrations of element B inthe free and attached states; and (4) the concentrations of element C in the free and attachedstates. Finally, the airborne concentration of each radon decay product will be evaluated as a sumof the respective concentrations in the free and attached states.

1 The recoil process is usually only considered for polonium-218 because of the substantial recoil energy (6 MeV)

associated with alpha decay.

C-15

TABLE C.1 Values of Rate Constants Used in the Radon Progeny Model

Symbol Name Value Unit

at Attachment rate 6.0 × 10-3 – 5.0 × 10-2 s-1

po Plate-out rate 3.0 × 10-4 – 6.0 × 10-2 s-1

Pat Probability of detachment from particles 0.50 -Ppo Probability of detachment from surfaces 0.25 -

Source: Bruno (1983).

C.2.1.1 Mass Balance of Element A � Free State

Under steady-state conditions, a mass balance of element A in the free state withincompartment i yields (see Equation A.23 in Appendix A):

( ) ,CV++QCCQ + CV = friipoatji

ij

j=fr

ifr

jji

ij

j=ii2

23

0223

01

20 λλλλ −∑−∑≠≠

(C.18)

where the terms related to the injection rate and the deposition-resuspension are neglected.Equation C.18 can be rewritten in the appropriate format to be used in the indoor air qualitymodel as:

( ) . C V = CQC Q + V++ iifr

jji

ij

j=fr

iji

ij

j=ipoat1

223

023

02 ∑−

∑

≠≠

(C.19)

C.2.1.2 Mass Balance of Element A � Attached State

A mass balance of element A in the attached state within compartment i yields:

,CV +

+

CVCVQCCQ + CV =

atii

R

diR

atiidi

atiiji

ij

j=at

iat

jji

ij

j=fr

iiat

2

2

222

30

2230

20

−−∑−∑≠≠

λλλλ

(C.20)

or

. C V = CQC Q + V +

+ friiat

atjji

ij

j=at

iji

ij

j=iR

Rdi

2230

230

22 1 λ

λλλλλ ∑−

∑

−

≠≠

(C.21)

C-16

C.2.1.3 Mass Balance of Element A � Plated-Out State

A mass balance of element A in the plated-out state within compartment i yields:

,CVCV = poii

friipo

22

20 λλ − (C.22)

or

. C = C fri

popoi

2

2

2

λλ (C.23)

C.2.1.4 Mass Balance of Element B � Free State

A mass balance of element B in the free state within compartment i yields:

( ) ,CV++QC

CQ + CVP + CVP + CV =

friipoatji

ij

j=fr

i

frjji

ij

j=po

iipoat

iiatfr

ii

33

30

3

330

23

23

230

λλλ

λλλ

−∑−

∑

≠

≠(C.24)

or

( )

. CVP + CVP + CV =

CQC Q + V++

poiipo

atiiat

frii

frjji

ij

=jfr

ijiij

=jipoat

23

23

23

330

3303

λλλ

λλλ ∑−

∑

≠≠

(C.25)

C.2.1.5 Mass Balance of Element B � Attached State

A mass balance of element B in the attached state within compartment i yields:

( )

,CV +

+ CV CV

QCCQ + CV + CVP =

atii

R

diRatiidi

atii

ji

ij

j=at

iat

jji

ij

j=fr

iiatat

iiat

3

3

333

30

3330

32310

−−

∑−∑−≠≠

λλλλλλ

λλ

(C.26)

or

C-17

( ) . CV + CVP - =

CQC Q + V +

+

friiat

atiiat

atjji

ij

=jat

ijiij

=jiR

Rdi

323

330

330

33

1

1

λλ

λλλλλ ∑−

∑

−

≠≠

(C.27)

C.2.1.6 Mass Balance of Element C � Free State

A mass balance of element C in the free state within compartment i yields:

( ) ,CV++QCCQ + CV = friipoatji

ij

=jfr

ifr

jjiij

=jfr

ii4

43

0443

03

40 λλλλ −∑−∑≠≠

(C.28)

or

( ) . CV = CQC Q + V++ frii

frjji

ij

=jfr

ijiij

=jipoat3

443

043

04 λλλλ ∑−

∑

≠≠

(C.29)

C.2.1.7 Mass Balance of Element C � Attached State

A mass balance of element C in the attached state within compartment i yields:

,C atiV i

R

diR + C atiV idiC at

iV i

Q ji

ij

=jC atiC at

jQ ji

ij

=j + C fr

iV iat + C atiV i = 0

44

444

30

4430

434

λ+λ

λλλ−λ−

∑

≠

−∑

≠

λλ

(C.30)

or

. CV + CV =

CQC Q + V +

+

friiat

atii

atjji

ij

=jat

ijiij

=jiR

Rdi

434

430

430

44 1

λλ

λλλλλ ∑−

∑

−

≠≠

(C.31)

C-18

C.3 WORKING LEVEL

Calculation of the WLi value associated with different radon isotopes follows a differentformulation depending on the radionuclide being considered. Thus, the WLi value incompartment i for an indoor atmosphere containing a mixture of radon (radon-222) progeny canbe evaluated as:

( ) ( ) ( ) , C. + C . + C . = WL iiii- 463626222Rn 107331007510031 −−− ××× (C.32)

where 2iC , ,3

iC and 4iC are the concentrations of polonium-218, lead-214, and bismuth-214,

respectively, in the indoor air of compartment i (pCi/m3). Similarly, for thoron (radon-220), theWLi value is evaluated as:

( ) ( ) ( ) , C. + C. + C. = WL iiii- 4534210220Rn 101711023110489 ′×′×′× −−− (C.33)

where Ci�2, Ci

�3, and Ci�4 are the concentrations of polonium-216, lead-212, and bismuth-212,

respectively, in the indoor air of compartment i (pCi/m3).

C.4 WORKING LEVEL MONTH

The normalized exposure to the radon progeny concentration for the exposure duration,ED, is measured in units of WLM, which for each compartment i can be calculated as:

,WLi F i F in ED

= WLM i

×

170

42 (C.34)

where

24 = number of hours per day (h/d),

170 = number of working hours per month (h/mo),

ED = exposure duration (d), and

iWL = average working level in compartment i for the exposure duration.

The fractions of time in Equation C.34 are defined in Section C.2. The indoor timefraction Fin and the outdoor time fraction Fout should sum up to 1. That is:

Fin + Fout = 1.0 . (C.35)

C-19

The time fraction in compartment i, Fi, can be less than, equal to, or greater than 1 in theRESRAD-BUILD code. When Fi is greater than 1, it can be used to calculate the collective dose.

The total exposure to the indoor airborne radon decay products is then evaluated bysumming Equation C.34 from all three compartments. That is:

( ). WLi F i1=i F in = WLM i=i = WLM ∑

×

∑ 3170

ED2431 (C.36)

Note that Equations C.34 and C.36 can be used to calculate the WLM from exposure toeither radon-222 or radon-220 progenies.

C.5 RADON PROGENY DOSIMETRY

The effective dose equivalent due to the exposure to radon decay products in the indoorair of each compartment i can be evaluated as:

,DCFWLMKD ii = (C.37)

where

Di = effective dose equivalent due to exposure to radon decay products (fromeither radon-222 or radon-220) in compartment i (mrem/yr),

DCF = dose conversion factor for the inhalation of radon decay products(mrem/WLM), and

K = multiplication factor to account for the extrapolation of doses fromuranium mines to homes.

For the radon-222 decay products, the values of the DCF and the K factor are equal to1,000 (mrem/WLM) and 0.76 (dimensionless), respectively. Similarly, for the radon-220 decayproducts, the values of the DCF and the K factor are equal to 350 (mrem/WLM) and 0.42(dimensionless), respectively.

The total effective dose equivalent resulting from the inhalation of airborne radon decayproducts is then given by summing the contribution from the occupancy of each compartment ofthe building. That is:

. DCF WLM K = D = D i=i∑31 (C.38)

If both radon-222 and radon-220 progenies are present in the indoor air, the final calculatedeffective dose equivalent should be the sum of the contribution from each decay series. That is:

. D + D = D 220Rn-222Rn-total (C.39)

C-20

C.6 REFERENCES

Bruno, R.C., 1983, “Verifying a Model of Radon Decay Product Behavior Indoors,” HealthPhysics 45:471.

Jacobi, W., 1972, “Activity and Potential Alpha Plan Energy of Radon 222 and Radon 220Daughters in Different Air Atmosphere,” Health Physics 22:331.

Porstendörfer, J., 1984, “Behavior of Radon Daughter Products in Indoor Air,” RadiationProtection Dosimetry 7:107.

Yu, C., et al., 2001, User’s Manual for RESRAD Version 6, ANL/EAD-4, Argonne NationalLaboratory, Argonne, Ill., Sept.

D-1

APPENDIX D:

INHALATION OF AIRBORNE RADIOACTIVE DUST

D-2

D-3

APPENDIX D:

INHALATION OF AIRBORNE RADIOACTIVE DUST

D.1 DUST RELEASE RATE

The inhalation pathway can be included in the building contamination model byperforming three sets of calculations:

• The mechanical removal of material from the source and the rate of release ofradionuclides into the indoor air of each compartment,

• The indoor airborne concentration of the radionuclides released into the air(using the indoor air quality model), and

• The inhalation of airborne radioactive dust and the associated effective doseequivalent.

For a volume source, the release rate of a principal radionuclide n into compartment i iscalculated by:

,24

)(000,10)(

tCAEftI

nsbssn

si

ρ= (D.1)

where

)(tI nsi = injection rate of radionuclide n into the indoor air of compartment i at

time t (pCi/h),

f = fraction of mechanically removed or eroded material that becomesairborne (air release fraction),

E = source removal or erosion rate (cm/d),

As = effective surface area of the source (m2),

bs = bulk density of the source material (g/cm3),

)(tC ns = radionuclide concentration in the source material (pCi/g) at time t,

24 = time conversion factor (number of hours per day) (h/d), and

10,000 = area conversion factor (cm2/m2).

D-4

For surface, line, and point sources, the release rate of a principal radionuclide n intocompartment i at time t is calculated by:

≥

<=

,0

24

)(

)(

R

RR

nsR

nSi

Tt

TtT

tfQf

tI (D.2)

where

fR = removable fraction of the source material,

f = fraction of removed material that becomes airborne (air releasefraction [ARF]),

TR = time to remove material from the source (lifetime) (d),

)(tQ ns = total radionuclide activity in the source (pCi) at time t, and

24 = time conversion factor (number of hours per day) (h/d).

The indoor air concentration, ),(tC ni at time t of each principal radionuclide n at each

compartment i of the building is calculated by using the indoor air quality model discussed inAppendix A.

D.2 INHALATION DOSE

The total committed effective dose equivalent )(tD nih from time t to t + ED due to the

inhalation of radionuclide n in the indoor air of compartment i, can be calculated with thefollowing equation:

,)()( nh

niiin

nih DCFEDtCIRFFtD = (D.3)

where

)(tD nih = total effective dose equivalent due to inhalation of radionuclide n in

compartment i from time t to t + ED (mrem),

ED = exposure duration (d),

Fin = fraction of time spent indoors (dimensionless),

Fi = fraction of indoor time that is spent at compartment i (dimensionless),

D-5

IR = inhalation rate (m3/d),

)(tC ni = average concentration of radionuclide n (pCi/m3) over the exposure

duration ED starting at time t in the indoor air of compartment i, and

nhDCF = inhalation dose conversion factor for radionuclide n (mrem/pCi).

The dose conversion factor nhDCF is discussed in Section D.3. The calculation of average

concentration, ( )tC ni , is discussed in Appendix H.

The total dose at time t from full occupancy of the building is evaluated as a sum of thedose at each compartment i at time t. That is:

( ) ( ) ( )∑ ∑= === 3

1

3

1.)()()(

i i

nii

nhin

nin

nth tCFEDDCFIRFtDtD (D.4)

D.3 DOSE CONVERSION FACTORS

The default inhalation dose conversion factors used in the RESRAD-BUILD code are thesame as those used in the RESRAD code (Yu et al. 2001). Values of dose conversion factors forinhalation were taken from a U.S. Environmental Protection Agency report (Eckerman et al.1988) and are listed in Table D.1. The values listed in Table D.1 are for dust particles with anactivity median aerodynamic diameter (AMAD) of 1 µm. Values for different inhalation classesare also listed in Table D.1. The inhalation class for inhaled radioactive material is definedaccording to the material’s rate of clearance from the lung. The three inhalation classes D, W,and Y correspond to retention half-times of less than 10 days, 10 to 100 days, and greater than100 days, respectively. If the inhalation class for a radionuclide is not known, the largest doseconversion factor for that radionuclide should be used. The default value for a radionuclide usedin the RESRAD-BUILD code is the largest dose conversion factor for that radionuclide.

D-6

TABLE D.1 Committed Effective Dose Equivalent Conversion Factors( n

hDCF ) for Inhalationa

RadionuclidebInhalation

Class

nhDCF

(mrem/pCi) RadionuclidebInhalation

Class

nhDCF

(mrem/pCi)

H-3 (H2O)c 6.40 × 10-8 Tc-99 D 1.02 × 10-6

C-14 (organic)c 2.09 × 10-6 W 8.33 × 10-6

(CO)c 2.90 × 10-9 Ru-106+D D 5.62 × 10-5

(CO2)c 2.35 × 10-8 W 1.18 × 10-4

Na-22 Dd 7.66 × 10-6 Y 4.77 × 10-4

Al-26 D 7.96 × 10-5 Ag-108m+D D 3.01 × 10-5

W 7.22 × 10-5 W 2.53 × 10-5

Cl-36 D 2.24 × 10-6 Y 2.83 × 10-4

W 2.19 × 10-5 Ag-110m+D D 3.96 × 10-5

K-40 D 1.24 × 10-5 W 3.09 × 10-5

Ca-41 W 1.35 × 10-6 Y 8.03 × 10-5

Mn-54 D 5.25 × 10-6 Cd-109 D 1.14 × 10-4

W 6.70 × 10-6 W 3.96 × 10-5

Fe-55 D 2.69 × 10-6 Y 4.51 × 10-5

W 1.34 × 10-6 Sb-125+D D 3.79 × 10-6

Co-57 W 2.63 × 10-6 W 1.39 × 10-5

Y 9.07 × 10-6 I-129 D 1.74 × 10-4

Co-60 W 3.31 × 10-5 Cs-134 D 4.63 × 10-5

Y 2.19 × 10-4 Cs-135 D 4.55 × 10-6

Ni-59 D 1.32 × 10-6 Cs-137+D D 3.19 × 10-5

W 9.18 × 10-7 Ce-144+D W 2.16 × 10-4

(vapor)c 2.70 × 10-6 Y 3.74 × 10-4

Ni-63 D 3.10 × 10-6 Pm-147 W 2.58 × 10-5

W 2.30 × 10-6 Y 3.92 × 10-5

(vapor)c 6.29 × 10-6 Sm-147 W 7.47 × 10-2

Zn-65 Y 2.04 × 10-5 Sm-151 W 3.00 × 10-5

Ge-68+D D 1.80 × 10-6 Eu-152 W 2.21 × 10-4

W 5.19 × 10-5 Eu-154 W 2.86 × 10-4

Sr-90+D D 2.47 × 10-4 Eu-155 W 4.14 × 10-5

Y 1.31 × 10-3 Gd-152 D 2.43 × 10-1

Nb-94 W 3.61 × 10-5 W 6.48 × 10-2

Y 4.14 × 10-4 Gd-153 D 2.38 × 10-5

D-7

TABLE D.1 (Cont.)

RadionuclidebInhalation

Class

nhDCF

(mrem/pCi) RadionuclidebInhalation

Class

nhDCF

(mrem/pCi)

Au-195 D 4.33 × 10-7 U-234 D 2.73 × 10-3

W 4.18 × 10-6 W 7.88 × 10-3

Y 1.30 × 10-5 Y 1.32 × 10-1

Tl-204 D 2.41 × 10-6 U-235+D D 2.54 × 10-3

Bi-207 D 3.23 × 10-6 W 7.29 × 10-3

W 2.00 × 10-5 Y 1.23 × 10-1

Pb-210+D D 2.32 × 10-2 U-236 D 2.59 × 10-3

Ra-226+D W 8.60 × 10-3 W 7.44 × 10-3

Ra-228+D W 5.08 × 10-3 Y 1.25 × 10-1

Ac-227+D D 6.72 U-238+D D 2.45 × 10-3

W 1.74 W 7.03 × 10-3

Y 1.31 Y 1.18 × 10-1

Th-228+D W 2.53 × 10-1 Np-237+D W 5.40 × 10-1

Y 3.45 × 10-1 Pu-238 W 3.92 × 10-1

Th-229+D W 2.16 Y 2.88 × 10-1

Y 1.75 Pu-239 W 4.29 × 10-1

Th-230 W 3.26 × 10-1 Y 3.08 × 10-1

Y 2.62 × 10-1 Pu-240 W 4.29 × 10-1

Th-232 W 1.64 Y 3.08 × 10-1

Y 1.15 Pu-241+D W 8.25 × 10-3

Pa-231 W 1.28 Y 4.96 × 10-3

Y 8.58 × 10-1 Pu-242 W 4.11 × 10-1

U-232 D 1.27 × 10-2 Y 2.93 × 10-1

W 1.49 × 10-2 Pu-244+D W 4.03 × 10-1

Y 6.59 × 10-1 Y 3.89 × 10-1

U-233 D 2.79 × 10-3 Am-241 W 4.44 × 10-1

W 7.99 × 10-3 Am-243+D W 4.40 × 10-1

Y 1.35 × 10-1 Cm-243 W 3.07 × 10-1

Cm-244 W 2.48 × 10-1

Cm-248 W 1.65Cf-252 W 1.37 × 10-1

Y 1.57 × 10-1

a Inhalation factors are for an AMAD of 1 µm.

b Dose conversion factors for entries labeled by “+D” are aggregated dose conversion factorsfor intake of a principal radionuclide together with radionuclides with a half-life greaterthan 10 minutes of the associated decay chain in secular equilibrium.

c Indicates a gaseous material.

d The three inhalation classes D, W, and Y correspond to retention half-times of less than10 days, 10 to 100 days, and greater than 100 days, respectively.

D-8

D.4 REFERENCES

Eckerman, K.F., et al., 1988, Limiting Values of Radionuclide Intake and Air Concentration andDose Conversion Factors for Inhalation, Submersion, and Ingestion, EPA-520/1-88-020, FederalGuidance Report No. 11, prepared by Oak Ridge National Laboratory, Oak Ridge, Tenn., forU.S. Environmental Protection Agency, Office of Radiation Programs, Washington, D.C.

Yu, C., et al., 2001, User’s Manual for RESRAD Version 6, ANL/EAD-4, Argonne NationalLaboratory, Argonne, Ill., July.

E-1

APPENDIX E:

INGESTION OF RADIOACTIVE MATERIAL

E-2

E-3

APPENDIX E:

INGESTION OF RADIOACTIVE MATERIAL

The ingestion pathway considered in the RESRAD-BUILD code includes (1) inadvertentingestion of removable (loose) material directly from the source and (2) inadvertent ingestion ofradioactive dust particulates deposited onto surfaces or food within the compartments of thebuilding.

E.1 DIRECT INGESTION OF REMOVABLE MATERIAL

The component of the total effective dose equivalent, )(tD nil at time t over the exposure

duration ED, due to the ingestion of loose material directly from the source in compartment icontaining radionuclide n, can be calculated by the following equations. For volume sources:

( ) ng

nsiin

nil DCFtCERFFEDtD )(24)( = , (E.1)

where

)(tD nil = component of the total effective dose equivalent due to ingestion of

loose material directly from the source containing radionuclide n attime t over the exposure duration, ED, in compartment i (mrem);

24 = time conversion factor (h/d);

ED = exposure duration (d);

Fin = fraction of time spent indoors (dimensionless);

Fi = fraction of indoor time spent at compartment i (dimensionless);

ER = ingestion rate of loose material directly from the source (g/h);

)(tC ns = average concentration of radionuclide n in the source material (pCi/g)

over the exposure duration, ED, starting at time t; and

ngDCF = ingestion dose conversion factor related to radionuclide n (mrem/pCi).

E-4

For surface, line, and point sources, the component of the total effective dose equivalent at time tover the exposure duration ED due to ingestion of loose material can be calculated as:

( ) ,DCF)t(QfERFFED)t(D ng

nsRliin

nil 24= (E.2)

where


ERl = ingestion rate of loose material directly from the source as a fraction ofthe source per unit time (1/h), and

)(tQns = total average radionuclide activity over the exposure duration, ED, in

the source (pCi) at time t.

The calculations of average concentration, )(tC ns and )(tQn

s , are discussed in Appendix H.

E.2 INGESTION OF DEPOSITED RADIOACTIVE DUST

The component of the total effective dose equivalent, )(tD nid , at time t over the exposure

duration ED due to the ingestion of radioactive dust particulates deposited onto surfaces ofcompartment i containing radionuclide n, can be given by the following equation:

( ) ,)(24)( ng

ndiiin

nid DCFtCSERFFEDtD = (E.3)

where

)(tD nid = component of the total effective dose equivalent due to ingestion of

deposited dust particulates containing radionuclide n in compartment iat time t over the exposure duration (mrem);

SER = surface ingestion rate or the ingestion rate of dust particulatesdeposited onto horizontal surfaces (m2/h);

)(tC ndi = average surface concentration of radionuclide n deposited onto

horizontal surfaces of compartment i (pCi/m2) over the exposureduration, ED, starting at time t; and

ngDCF = ingestion dose conversion factor for radionuclide n (mrem/pCi).

E-5

The total ingestion dose, ),(tD ni over the exposure duration at time t is evaluated as a sum of the

dose contribution from both components, nieD and ,n

idD listed above. Calculation of )(tC ndi is

discussed in Appendix H.

E.3 DOSE CONVERSION FACTORS

The ingestion dose conversion factors used in the RESRAD-BUILD code are the same asthose used in the RESRAD code (Yu et al. 2001). Values of dose conversion factors for ingestionwere taken from a U.S. Environmental Protection Agency report (Eckerman et al. 1988) and aretabulated in Table E.1. Dose conversion factors depend on the chemical form, which determinesthe fraction f1 of a radionuclide entering the gastrointestinal (GI) tract that reaches body fluids.Data on the appropriate fractions for different chemical forms are given in Publication 30 of theInternational Commission on Radiological Protection (1979–1982). The dose conversion factorsused in RESRAD-BUILD are the values corresponding to the largest values of f1 in Table E.1

E-6

TABLE E.1 Committed Effective Dose Equivalent Conversion Factors ( ngDCF ) for

Internal Radiation from Ingestion

Radionuclidea f1b

ngDCF

(mrem/pCi) Radionuclidea f1b

ngDCF

(mrem/pCi)

H-3 1.0 6.40 × 10-8 Pm-147 3.00 × 10-4 1.05 × 10-6

C-14 1.0 2.09 × 10-6 Sm-147 3.00 × 10-4 1.85 × 10-4

Na-22 1.0 1.15 × 10-5 Sm-151 3.00 × 10-4 3.89 × 10-7

Al-26 1.00 × 10-2 1.46 × 10-5 Eu-152 1.00 × 10-3 6.48 × 10-6

Cl-36 1.0 3.03 × 10-6 Eu-154 1.00 × 10-3 9.55 × 10-6

K-40 1.0 1.86 × 10-5 Eu-155 1.00 × 10-3 1.53 × 10-6

Ca-41 3.00 × 10-1 1.27 × 10-6 Gd-152 3.00 × 10-4 1.61 × 10-4

Mn-54 1.00 × 10-1 2.77 × 10-6 Gd-153 3.00 × 10-4 1.17 × 10-6

Fe-55 1.00 × 10-1 6.07 × 10-7 Au-195 1.00 × 10-1 1.06 × 10-6

Co-57 3.00 × 10-1 1.18 × 10-6 Tl-204 1.0 3.36 × 10-6

5.00 × 10-2 7.44 × 10-7 Bi-207 5.00 × 10-2 5.48 × 10-6

Co-60 3.00 × 10-1 2.69 × 10-5 Pb-210+D 2.00 × 10-1 7.27 × 10-3

5.00 × 10-2 1.02 × 10-5 Po-210 1.00 × 10-1 1.90 × 10-3

Ni-59 5.00 × 10-2 2.10 × 10-7 Ra-226+D 2.00 × 10-1 1.33 × 10-3

Ni-63 5.00 × 10-2 5.77 × 10-7 Ra-228+D 2.00 × 10-1 1.44 × 10-3

Zn-65 5.00 × 10-1 1.44 × 10-5 Ac-227+D 1.00 × 10-3 1.48 × 10-2

Ge-68+D 1.0 1.41 × 10-6 Th-228+D 2.00 × 10-4 8.08 × 10-4

Sr-90+D 3.00 × 10-1 1.53 × 10-4 Th-229+D 2.00 × 10-4 4.03 × 10-3

1.00 × 10-2 2.28 × 10-5 Th-230 2.00 × 10-4 5.48 × 10-4

Nb-94 1.00 × 10-2 7.14 × 10-6 Th-232 2.00 × 10-4 2.73 × 10-3

Tc-99 8.00 × 10-1 1.46 × 10-6 Pa-231 1.00 × 10-3 1.06 × 10-2

Ru-106+D 5.00 × 10-2 2.74 × 10-5 U-232 5.00 × 10-2 1.31 × 10-3

Ag-108m+D 5.00 × 10-2 7.62 × 10-6 2.00 × 10-3 6.92 × 10-5

Ag-110m+D 5.00 × 10-2 1.08 × 10-5 U-233 5.00 × 10-2 2.89 × 10-4

Cd-109 5.00 × 10-2 1.31 × 10-5 2.00 × 10-3 2.65 × 10-5

Sb-125+D 1.00 × 10-1 3.65 × 10-6 U-234 5.00 × 10-2 2.83 × 10-4

1.00 × 10-2 3.64 × 10-6 2.00 × 10-3 2.61 × 10-5

I-129 1.0 2.76 × 10-4 U-235+D 5.00 × 10-2 2.67 × 10-4

Cs-134 1.0 7.33 × 10-5 2.00 × 10-3 2.81 × 10-5

Cs-135 1.0 7.07 × 10-6 U-236 5.00 × 10-2 2.69 × 10-4

Cs-137+D 1.0 5.00 × 10-5 2.00 × 10-3 2.47 × 10-5

Ce-144+D 3.00 × 10-4 2.11 × 10-5

E-7

TABLE E.1 (Cont.)

Radionuclidea f1b

ngDCF

(mrem/pCi) Radionuclidea f1b

ngDCF

(mrem/pCi)

U-238+D 5.00 × 10-2 2.69 × 10-4 1.00 × 10-5 7.66 × 10-7

2.00 × 10-3 3.74 × 10-5 Pu-242 1.00 × 10-3 3.36 × 10-3

Np-237+D 1.00 × 10-3 4.44 × 10-3 1.00 × 10-4 3.50 × 10-4

Pu-238 1.00 × 10-3 3.20 × 10-3 1.00 × 10-5 4.92 × 10-5

1.00 × 10-4 3.36 × 10-4 Pu-244+D 1.00 × 10-3 3.32 × 10-3

1.00 × 10-5 4.96 × 10-5 1.00 × 10-4 3.60 × 10-4

Pu-239 1.00 × 10-3 3.54 × 10-3 1.00 × 10-5 6.32 × 10-5

1.00 × 10-4 3.69 × 10-4 Am-241 1.00 × 10-3 3.64 × 10-3

1.00 × 10-5 5.18 × 10-5 Am-243+D 1.00 × 10-3 3.63 × 10-3

Pu-240 1.00 × 10-3 3.54 × 10-3 Cm-243 1.00 × 10-3 2.51 × 10-3

1.00 × 10-4 3.69 × 10-4 Cm-244 1.00 × 10-3 2.02 × 10-3

1.00 × 10-5 5.18 × 10-5 Cm-248 1.00 × 10-3 1.36 × 10-2

Pu-241+D 1.00 × 10-3 6.85 × 10-5 Cf-252 1.00 × 10-3 1.08 × 10-3

1.00 × 10-4 6.92 × 10-6

a Dose conversion factors for entries labeled “+D” are aggregated dose conversion factors for intake ofa principal radionuclide together with radionuclides with a half-life greater than 10 minutes of theassociated decay chain in secular equilibrium.

b Fraction of a stable element entering the GI tract that reaches body fluids.

E-8

E.4 REFERENCES

Eckerman, K.F., et al., 1988, Limiting Values of Radionuclide Intake and Air Concentration andDose Conversion Factors for Inhalation, Submersion, and Ingestion, EPA-520/1-88-020, FederalGuidance Report No. 11, prepared by Oak Ridge National Laboratory, Oak Ridge, Tenn., forU.S. Environmental Protection Agency, Office of Radiation Programs, Washington, D.C.

International Commission on Radiological Protection, 1979-1982, Limits for Intakes ofRadionuclides by Workers, a report of Committee 2 of the International Commission onRadiological Protection, adopted by the Commission in July 1978, ICRP Publication 30, Part 1(and Supplement), Part 2 (and Supplement), Part 3 (and Supplements A and B), and Index,Annals of the ICRP, Pergamon Press, New York, N.Y.

Yu, C., et al., 2001, User’s Manual for RESRAD Version 6.0, ANL/EAD-4, Argonne NationalLaboratory, Argonne, Ill., July.

F-1

APPENDIX F:

EXTERNAL RADIATION EXPOSURE

F-2

F-3

APPENDIX F:

EXTERNAL RADIATION EXPOSURE

The external radiation exposure model is used to calculate the effective doses from(1) direct external exposure to the sources, (2) external exposure to deposited material (modeledas an area source), and (3) external exposure to radioactive dust in the indoor air (airsubmersion). For the air submersion and deposition pathways (2 and 3), the exposure to thereceptor is from the radioactive air concentration in the same room only.

Two direct exposure models based on the geometrical type of sources are used. Themodel for the point and line contamination is a simple dose integral method. The model for areaand volume sources is based on a semiinfinite slab source, with corrections for geometricalfactors.

The volume source can have up to five layers, with any one layer being contaminated.The exposure model uses the methodology described by Kamboj et al. (1998, 2002) forcorrections due to finite size with extension to include differences due to the source material. Thearea source is treated as a volume source of small thickness (0.01 cm) with unit density. Theexternal exposure from the material deposited on the floor is estimated by treating the floor as anarea source with the receptor located at 1 m above the center of the floor. The correction for sizeis applied to account for the finite dimensions of the floor.

F.1 EXTERNAL DOSE FROM CONTAMINATED VOLUME SOURCE

The total external dose at time t over the exposure duration, ED, from exposure to a

volume source containing radionuclide n in compartment i, )t(DniV , is expressed as:

,F DCF )(C FF)/ED( = )t(D nG

nv

nsViin

niV t365 (F.1)

where


365 = time conversion factor (d/yr);

Fin = fraction of time spent indoors;

Fi = fraction of time spent in compartment i;

nvDCF = FGR-12 dose conversion factor for infinite volume source

[(mrem/yr)/(pCi/g)];

F-4

GnF = geometrical factor for finite area, source thickness, shielding, source

material, and position of receptor relative to the source forradionuclide n; and

)(tC nsV = average volume source concentration (pCi/g) of radionuclide n over

the exposure duration, ED, starting at time t.

The calculation of )(tC nsV is discussed in Appendix H.

The geometrical factor, FG, is the ratio of the effective dose equivalent for the actualsource to the effective dose equivalent for the standard source. The standard source is acontaminated soil of infinite depth and lateral extent with no cover. The geometrical factor isexpressed as the product of the depth-and-cover factor, FCD, an area and material factor, FAM,and the off-set factor, FOFF-SET.

Dose conversion factors in Federal Guidance Report-12 (FGR-12) (Eckerman and Ryman1993) are given for surface and uniformly distributed volume sources at four specific thickness(1, 5, 15 cm, and effectively infinite) with a soil density of 1.6 g/cm3. FGR-12 assumes thatsources are infinite in lateral extent. In actual situations, sources can have any depth, shape,cover, and size. A depth-and-cover factor function, FCD, was developed with regression analysisto express the attenuation for radionuclides. Three independent radionuclide-specific parameterswere determined by using the effective dose equivalent values of FGR-12 at different depths.Kamboj et al. (1998) describe how the depth-and-cover factor function was derived using theeffective dose equivalent values of FGR-12 at different depths. A depth-and-cover factorfunction was derived from the depth factor function by considering both dose contribution andattenuation from different depths:

( )( ) ( ) ( ),eBeeAe

T,TD

tT,tTDF sSBccBSSAccA tKtKtKtK

Sc

sSccCD

ρ−ρ−ρ−ρ− −+−=∞==

=== 11

0(F.2)

where

A, B = fit parameters (dimensionless);

KA, KB = fit parameters (cm2/g);

tc = shielding thickness (cm) (it is the sum of all shielding thicknessesbetween the source and the receptor; the shielding is placedimmediately adjacent to the source);

ρc = shielding density (g/cm3) (it is the thickness averaged density betweenthe source and receptor);

F-5

ts = source thickness (cm);

ρs = source density (g/cm3);

Tc = shielding parameter; and

Ts = source depth parameter.

The following three constraints were put on the four fitting parameters:

1. All the parameters are forced to be positive.

2. A + B = 1.

3. In the limit source depth, ts = zero; the DCF should match the contaminatedsurface DCF.

Fitted values for all the four unknown parameters (A, B, KA, KB) were found for67 radionuclides available in the RESRAD-BUILD computer code and are listed in Table F.1.

For actual geometries (finite area and different materials), the area and material factor,FAM, was derived by using the point-kernel method. This factor depends not only on the lateralextent of the contamination but also on source thickness, shielding thickness, gamma energies,and source material through its attenuation and buildup factors. All energies from radionuclidedecay are considered separately and weighted by its yield y, energy E, and an energy-dependentcoefficient K to convert from air-absorbed dose to effective dose equivalent:

( )( )( )( )

,

dVx

exBKEy

Vdx

exBKEy

F

j:EnergiesV

x

jjj

j:EnergiesV

x

jjj

AM

∑ ∫

∑ ∫µ−

′

′µ−′

′

′

=

2

2

(F.3)

where at source thickness t,

( ) ( )222 tttrx ca +++=′ , (F.4)

( ) ( )222 100 trx ++= (F.5)

( )( )ttt

ttt

ca

sccaa

++++= µµµµ (F.6)

F-6

TABLE F.1 Fitted Parameters Ai, Bi, KAi, and KBi Used to CalculateDepth and Cover Factors for 67 Radionuclides

Radionuclide Ai Bi KAi KBi

H-3 0.00 0.00 0.00 0.00C-14 6.421 × 10-1 3.579 × 10-1 2.940 × 10-1 3.369Na-22 9.263 × 10-1 7.37 × 10-2 8.74 × 10-2 1.331Al-26 9.276 × 10-1 7.24 × 10-2 7.94 × 10-2 1.284Cl-36 8.885 × 10-1 1.115 × 10-1 1.325 × 10-1 1.886K-40 7.26 × 10-2 9.274 × 10-1 1.269 7.70 × 10-2

Ca-41 0.00 0.00 0.00 0.00Mn-54 8.48 × 10-2 9.152 × 10-1 1.215 8.79 × 10-2

Fe-55 0.00 0.00 0.00 0.00Co-57 9.288 × 10-1 7.12 × 10-2 1.604 × 10-1 1.671Co-60 9.235 × 10-1 7.65 × 10-2 7.83 × 10-2 1.263Ni-59 0.00 0.00 0.00 0.00Ni-63 0.00 0.00 0.00 0.00Zn-65 9.271 × 10-1 7.29 × 10-2 8.37 × 10-2 1.327

Ge-68+Da 9.270 × 10-1 7.30 × 10-2 9.94 × 10-2 1.412Sr-90+D 9.074 × 10-1 9.260 × 10-2 1.202 × 10-1 1.699Nb-94 9.275 × 10-1 7.250 × 10-2 9.10 × 10-2 1.378Tc-99 7.871 × 10-1 2.129 × 10-1 2.106 × 10-1 2.589Ru-106+D 9.271 × 10-1 7.290 × 10-2 9.57 × 10-2 1.409Ag-108m+D 9.282 × 10-1 7.180 × 10-2 9.67 × 10-2 1.442Ag-110m+D 9.261 × 10-1 7.390 × 10-2 8.74 × 10-2 1.339Cd-109 6.534 × 10-1 3.466 × 10-1 2.047 × 10-1 4.753Sb-125+D 9.273 × 10-1 7.270 × 10-2 1.005 × 10-1 1.507I-129 4.350 × 10-1 5.650 × 10-1 7.137 × 10-1 3.555Cs-134 9.266 × 10-1 7.34 × 10-2 9.26 × 10-2 1.379Cs-135 7.254 × 10-1 2.746 × 10-1 2.508 × 10-1 3.030Cs-137+D 9.281 × 10-1 7.19 × 10-2 9.47 × 10-2 1.411Ce-144+D 9.116 × 10-1 8.84 × 10-2 9.38 × 10-2 1.411Pm-147 7.726 × 10-1 2.274 × 10-1 2.087 × 10-1 2.780Sm-147 0.00 0.00 0.00 0.00Sm-151 3.540 × 10-2 9.646 × 10-1 8.270 × 10-1 6.15Eu-152 9.100 × 10-1 9.000 × 10-2 8.40 × 10-2 1.185Eu-154 8.939 × 10-1 1.061 × 10-1 8.25 × 10-1 1.008Eu-155 8.569 × 10-1 1.431 × 10-1 1.912 × 10-1 1.486Gd-152 0.00 0.00 0.00 0.00Gd-153 8.226 × 10-1 1.774 × 10-1 1.986 × 10-1 1.983Au-195 8.772 × 10-1 1.228 × 10-1 2.380 × 10-1 1.880Tl-204 8.679 × 10-1 1.321 × 10-1 2.068 × 10-1 1.923Bi-207 9.246 × 10-1 7.540 × 10-2 8.89 × 10-2 1.350Pb-210+D 7.502 × 10-1 2.498 × 10-1 1.753 × 10-1 2.200Ra-226+D 9.272 × 10-1 7.280 × 10-2 8.35 × 10-2 1.315Ra-228+D 9.266 × 10-1 7.340 × 10-2 8.77 × 10-2 1.371Ac-227+D 9.229 × 10-1 7.710 × 10-2 1.172 × 10-1 1.512Th-228+D 9.277 × 10-1 7.230 × 10-2 7.55 × 10-2 1.262Th-229+D 9.130 × 10-1 8.700 × 10-2 1.130 × 10-1 1.491Th-230+D 8.628 × 10-1 1.372 × 10-1 1.871 × 10-1 4.033

F-7

TABLE F.1 (Cont.)

Radionuclide Ai Bi KAi KBi

Th-232 8.152 × 10-1 1.848 × 10-1 2.082 × 10-1 5.645Pa-231 9.295 × 10-1 7.050 × 10-2 1.163 × 10-1 2.014U-232 8.086 × 10-1 1.914 × 10-1 1.754 × 10-1 6.021U-233 8.889 × 10-1 1.112 × 10-1 1.394 × 10-1 4.179U-234 7.229 × 10-1 2.771 × 10-1 1.937 × 10-1 7.238U-235+D 9.292 × 10-1 7.080 × 10-2 1.383 × 10-1 1.813U-236 5.932 × 10-1 4.068 × 10-1 1.980 × 10-1 8.379U-238+D 8.590 × 10-1 1.410 × 10-1 9.19 × 10-2 1.111Np-237+D 9.255 × 10-1 7.450 × 10-2 1.228 × 10-1 1.671Pu-238 2.972 × 10-1 7.028 × 10-1 1.958 × 10-1 9.011Pu-239 8.002 × 10-1 1.998 × 10-1 1.348 × 10-1 6.550Pu-240 2.977 × 10-1 7.023 × 10-1 2.176 × 10-1 8.997Pu-241+D 9.132 × 10-1 8.680 × 10-2 1.582 × 10-1 2.027Pu-242 3.314 × 10-1 6.686 × 10-1 2.109 × 10-1 8.982Pu-244+D 9.259 × 10-1 7.410 × 10-2 9.26 × 10-2 1.431Am-241 8.365 × 10-1 1.635 × 10-1 3.130 × 10-1 2.883Am-243+D 9.098 × 10-1 9.020 × 10-2 1.473 × 10-1 1.642Cm-243 9.247 × 10-1 7.530 × 10-2 1.350 × 10-1 1.662Cm-244 7.0 × 10-3 9.930 × 10-1 8.461 × 10-2 2.194Cm-248 7.333 × 10-1 2.667 × 10-1 1.042 × 101 1.215Cf-252 6.505 × 10-1 3.495 × 10-1 7.259 1.82 × 10-1

a +D means that associated decay product radionuclides with half-lives lessthan six month are also included.

( )

++

++

++

= xttt

tBx

ttt

tBx

ttt

tBxB

cas

ca

cc

ca

aa (F.7)

where B and µ are the buildup factor and the attenuation factor for the appropriate material (a forair, c for shield material, and s for source material or soil reference). The integration volume V´is the desired geometry of specified material with radius r, shielding thickness tc, and airthickness ta, whereas V is the reference geometry of soil extending infinitely laterally with noshielding and the receptor midpoint located 1 m from the surface.

The off-set factor, FOFF-SET, is the ratio of the dose estimates from a noncircular shapedcontaminated material to a reference shape. The concept of the shape factor is used to calculatethe off-set factor. The reference shape is a fully contaminated circular area encompassing thegiven shape, centered about the receptor. This factor is derived by considering the area, materialfactors of a series of concentric circles, and the corresponding contamination fraction of theannular regions. The off-set factor is obtained by enclosing the irregularly shaped contaminatedarea in a circle, multiplying the area factor of each annulus by the fraction of the contaminated

F-8

annulus area, fi, summing the products, and dividing by the area factor of a circular contaminatedmaterial that is equivalent in area:

( ) ( )[ ]

( ),

11

11

−

−=

∑

∑

=−

=−

− n

iiiiA

n

iiAiAi

SETOFF

AAfF

AFAFfF (F.8)

where FA(Ai) is the area factor for circular area Ai of a given source thickness and coverthickness.

F.2 EXTERNAL DOSE FROM CONTAMINATED POINT SOURCE

The model for point sources is simply expressed considering the energy of the radiationand attenuation. The total external dose over the exposure duration, ED, from exposure to a point

source containing radionuclide n, in compartment i, )t(Dnip at time t, is:

( ) ( ) ( ) ( ),

424

2a

tt

airj

njenaanjnj

nsPiin

niP

t

eEdtBEytCFFEDtD

ccaa

πρµ

µµµ −−

∑

= (F.9)

where

24 = time conversion factor (h/d);


)t(C nsP = average total activity of radionuclide n in the source over the

exposure duration starting at time t (pCi);

ynj = yield for gamma j from radionuclide n;

Enj = energy for gamma j from radionuclide n (MeV);

d = unit dose rate per energy absorption; and

ρ

µ )E( njen

air

= mass energy absorption coefficient in air (cm2/g).

The calculation of average total activity )(tC nsp is discussed in Appendix H.

F-9

F.3 EXTERNAL DOSE FROM CONTAMINATED LINE SOURCE

The model for line sources differs from that of the point source in the more complicatedgeometrical factor. The total external dose over the exposure duration from exposure to a linesource in compartment i, containing radionuclide n, )(tD n

iL at time t, is expressed as:

,A )E(

d )(z B E y )t(C FF ED = (t)D Lnjen

air njnj

j

nsLiin

niL

ρ

µ′∑24 (F.10)

aatz ′µ=′ (F.11)

,dx)t+x(4

e e = A 2a

2

t+x -

line

t-L

2a

2a

cc

π

µµ ∫ (F.12)

where

)(tC nsL = average line source concentration of radionuclide n over the exposure duration

ED starting at time t (pCi/m),

ta = perpendicular distance to receptor, and

at ′ = distance from the receptor to the midpoint of the line source.

These geometrical parameters are shown in Figure F.1 and are calculated on the basis of theinput geometrical parameters of the source and the location of the receptor. The calculation of

)(tC nsL is discussed in Appendix H.

FIGURE F.1 Geometry in the Line Source Model

F-10

F.4 EXTERNAL DOSE FROM CONTAMINATED DUST IN INDOOR AIR

The total air submersion external dose over the exposure duration, ED, ),(, tDnsubi at time t

from exposure to indoor contaminated dust in the air is calculated by using the followingequation:

,DCF)t(CFF)/ED()t(D nsub

niiin

nsub,i 365= (F.13)

where


365 = time conversion factor (d/yr);

)(, tDnsubi = total air submersion effective dose equivalent over the exposure

duration, ED, from radionuclide n at time t in compartment i (mrem);

)(tC ni = average concentration of radionuclide n over the exposure duration,

ED, starting at time t in the indoor air of compartment i (pCi)/m3); and

nsubDCF = air submersion dose conversion factor for radionuclide n (mrem/yr

per pCi/m3).

The nsubDCF is for a semi-infinite cloud source; no correction (reduction) for the finite indoor air

volume was performed in the RESRAD-BUILD code. The calculation of )(tC ni is discussed in

Appendix H.

F.5 DOSE CONVERSION FACTORS

Values of dose conversion factors for external exposure were taken from aU.S. Environmental Protection Agency report (Eckerman and Ryman 1993). Table F.2 lists thedose conversion factors for the surface (infinite plane) source, the infinite depth volume source,and the air submersion exposure.

F-11

TABLE F.2 Effective Dose Equivalent Conversion Factors (DCFi1) forExternal Gamma Radiation from Contaminated Ground

RadionuclideSurface Factorsa

(mrem/yr)/(pCi/cm2)Volume Factorsb

(mrem/yr)/(pCi/g)Submersionc

(mrem/yr)/(pCi/m3)

H-3 0.00 0.00 0.0C-14 1.88 × 10-5 1.34 × 10-5 2.62 × 10-8

Na-22 2.46 1.34 × 101 1.26 × 10-2

Al-26 2.91 1.74 × 101 1.59 × 10-2

Cl-36 7.87 × 10-4 2.39 × 10-3 2.61 × 10-6

K-40 1.71 × 10-1 1.04 9.42 × 10-4

Ca-41 0.00 0.00 0Mn-54 9.50 × 10-1 5.16 4.79 × 10-3

Fe-55 0.00 0.00 0Co-57 1.35 × 10-1 5.01 × 10-1 6.56 × 10-4

Co-60 2.75 1.62 × 101 1.47 × 10-2

Ni-59 0.00 0.00 0Ni-63 0.00 0.00 0Zn-65 6.47 × 10-1 3.70 3.39 × 10-3

Ge-68+Dc 1.10 5.62 5.36 × 10-3

Sr-90+D 6.56 × 10-3 2.46 × 10-2 2.31 × 10-5

Nb-94 1.79 9.68 9.01 × 10-3

Tc-99 9.13 × 10-5 1.26 × 10-4 1.90 × 10-7

Ru-106+D 2.48 × 10-1 1.29 1.22 × 10-3

Ag-108m+D 1.87 9.65 9.14 × 10-3

Ag-110m+D 3.10 1.72 × 101 1.59 × 10-2

Cd-109 2.63 × 10-2 1.47 × 10-2 3.44 × 10-5

Sb-125+D 5.07 × 10-1 2.45 2.38 × 10-3

I-129 3.02 × 10-2 1.29 × 10-2 4.45 × 10-5

Cs-134 1.78 9.47 8.86 × 10-3

Cs-135 3.90 × 10-5 3.83 × 10-5 6.61 × 10-8

Cs-137+D 6.49 × 10-1 3.41 3.19 × 10-3

Ce-144+D 6.82 × 10-2 3.24 × 10-1 3.29 × 10-4

Pm-147 3.99 × 10-5 5.01 × 10-5 8.11 × 10-8

Sm-147 0.00 0.00 0Sm-151 5.89 × 10-6 9.84 × 10-7 4.22 × 10-9

Eu-152 1.29 7.01 6.61 × 10-3

Eu-154 1.39 7.68 7.18 × 10-3

Eu-155 6.90 × 10-2 1.82 × 10-1 2.91 × 10-4

Gd-152 0.00 0.00 0Gd-153 1.24 × 10-1 2.45 × 10-1 4.34 × 10-4

Au-195 9.17 × 10-2 2.07 × 10-1 3.76 × 10-4

Tl-204 1.73 × 10-3 4.05 × 10-3 6.54 × 10-6

Bi-207 1.73 9.38 8.82 × 10-3

Pb-210+D 4.14 × 10-3 6.12 × 10-3 1.05 × 10-5

Ra-226+D 1.94 1.12 × 101 1.04 × 10-2

Ra-228+D 1.09 5.98 5.59 × 10-3

Ac-227+D 4.53 × 10-1 2.01 2.16 × 10-3

Th-228+D 1.64 1.02 × 101 9.41 × 10-3

Th-229+D 3.70 × 10-1 1.60 1.72 × 10-3

F-12

TABLE F.2 (Cont.)

RadionuclideSurface Factorsa

(mrem/yr)/(pCi/cm2)Volume Factorsb

(mrem/yr)/(pCi/g)Submersionc

(mrem/yr)/(pCi/m3)

Th-230+D 8.78 × 10-4 1.21 × 10-3 2.04 × 10-6

Th-232 6.45 × 10-4 5.21 × 10-4 1.02 × 10-6

Pa-231 4.76 × 10-2 1.91 × 10-1 2.01 × 10-4

U-232 1.18 × 10-3 9.02 × 10-4 1.66 × 10-6

U-233 8.38 × 10-4 1.40 × 10-3 1.91 × 10-6

U-234 8.75 × 10-4 4.02 × 10-4 8.93 × 10-7

U-235+D 1.95 × 10-1 7.57 × 10-1 9.03 × 10-4

U-236 7.61 × 10-4 2.15 × 10-4 5.86 × 10-7

U-238+D 3.53 × 10-2 1.52 × 10-1 1.60 × 10-4

Np-237+D 2.62 × 10-1 1.10 1.21 × 10-3

Pu-238 9.80 × 10-4 1.51 × 10-4 5.71 × 10-7

Pu-239 4.29 × 10-4 2.95 × 10-4 4.96 × 10-7

Pu-240 9.40 × 10-4 1.47 × 10-4 5.56 × 10-7

Pu-241+D 6.07 × 10-6 1.89 × 10-5 2.56 × 10-8

Pu-242 7.80 × 10-4 1.28 × 10-4 4.69 × 10-7

Pu-244+D 3.88 × 10-1 2.02 1.90 × 10-3

Am-241 3.22 × 10-2 4.37 × 10-2 9.57 × 10-5

Am-243+D 2.53 × 10-1 8.95 × 10-1 1.15 × 10-3

Cm-243 1.46 × 10-1 5.83 × 10-1 6.88 × 10-4

Cm-244 1.03 × 10-3 1.26 × 10-4 5.74 × 10-7

Cm-248 7.02 × 10-4 8.78 × 10-5 3.97 × 10-7

Cf-252 8.45 × 10-4 1.76 × 10-4 5.92 × 10-7

a Surface factors represent infinite thinness.

b Volume factors represent infinite depth.

c Effective dose equivalent conversion factors for entries labeled with "+D" areaggregated factors of a principal radionuclide, together with the associatedradionuclides with half-lives less than six month.

F.6 REFERENCES

Eckerman, K.F., and J.C. Ryman, 1993, External Exposure to Radionuclides in Air, Water, andSoil, Exposure-to-Dose Coefficients for General Application, Based on the 1987 FederalRadiation Protection Guidance, Federal Guidance Report No. 12, prepared by Oak RidgeNational Laboratory, Oak Ridge, Tenn., for U.S. Environmental Protection Agency.

Kamboj, S., et al., 1998, External Exposure Model Used in the RESRAD Code for VariousGeometries of Contaminated Soil, ANL/EAD/TM-84, Argonne National Laboratory, Argonne,Ill., Sept.

Kamboj, S., et al., 2002, “External Exposure Model in the RESRAD Computer Code,” HealthPhysics 82(6):831−839.

G-1

APPENDIX G:

EXPOSURES TO TRITIUM IN BUILDINGS

G-2

G-3

APPENDIX G:

EXPOSURES TO TRITIUM IN BUILDINGS

G.1 INTRODUCTION

Except for radon, most of the radionuclides considered in the RESRAD-BUILD code arein solid forms that adsorb to building material. Consequently, these radionuclides would only beavailable for inhalation or ingestion as the result of mechanical forces or the weathering process.These actions would erode or loosen the contaminated building material so that it would bedispersed into the indoor air and be inhaled, or the material would attach to the hands of a humanreceptor and inadvertently be ingested. Tritium contamination requires special consideration,because in addition to erosion, tritium, which most often is in the chemical form of tritiated water(HTO), can vaporize and diffuse out of the building material and reach the indoor air. Theamount of vaporization and the vaporization rate depend on the amount of free HTO molecules(i.e., those trapped in pore spaces and not incorporated into the building material) in the building(source) material. This appendix discusses the methodology used to estimate tritium exposuresfrom various pathways, as well as a transport model developed for evaluating the tritium releaserate caused by vaporization from a volume contamination source. While the transport modelfocuses on tritium in the chemical form of HTO, the methodology used to estimate tritiumexposures from different pathways is similar to that used for other radionuclides and, therefore,can be applied to consider exposures to tritium in other chemical forms (such as tritiated organiccompounds and metal tritides) that adsorb to building material.

G.2 SURFACE SOURCES

The surface sources defined in this section are the point, line, and area sources. Volumesources are discussed in Section G.3. The external radiation dose for tritium is essentially zero,because tritium emits only low-energy beta radiation. Radiation exposures to tritium from theinhalation and ingestion pathways are evaluated in the same manner as those exposures to otherradionuclides. Exposures to other radionuclides are discussed in Appendixes D and E. Onepathway that is unique to tritium is exposure through dermal absorption. This pathway isdiscussed in Section G.2.3.

G.2.1 Inhalation

For surface sources, potential tritium exposures through the inhalation pathway areconsidered through the “removable fraction (fR),” “air release fraction (f),” and “source lifetime(TR)” parameters. These three parameters are used in Equation D.2 in Appendix D to estimatethe injection rate of tritium into the indoor air, which is then used in the indoor air quality modelto estimate the air concentration of tritium in each building compartment. Whether the releasedtritium is in vapor or solid form would depend on the chemical form of the contaminant; theform would need to be determined to select the proper input values for these three parameters.

G-4

Tritium in the chemical form of HTO is most likely to be released in vapor form (free HTO),unless it is incorporated into the entity of the building material through molecular exchange,which would prohibit the vaporization of HTO.

For solid radionuclides that are assumed to adsorb to the source material, the removablefraction is the same as the source material. However, for tritium in a chemical form that canvaporize easily, the removable fraction should be greater than the removable fraction of thesource material. In general, when considering tritium in the form of HTO, a removable fractionof 1 is recommended for yielding conservative results. Realistically, however, not all the HTOwill vaporize through molecular exchange; some of the tritium may be incorporated into theentity of the building material. A value of 0.1 was used by both the International Organizationfor Standardization (ISO 1988) and the U.S. Department of Energy (DOE 1991) whenconsidering the release of tritium in a generic situation (i.e., tritium in different chemical formsand from different contamination sources).

When in the form of HTO, tritium can be released through vaporization without thesource material being removed; the “removable fraction” parameter should be assigned a valueof 1 for the dose calculation.

The “source lifetime” parameter is used to determine the release rate of tritium to theindoor air. The elapsed time for free HTO molecules that escape from the source throughvaporization would be very small. For tritium in a solid form, the elapsed time would depend onthe weathering process or the potential mechanical forces that remove the source material.

G.2.2 Ingestion

RESRAD-BUILD considers both direct ingestion and secondary ingestion ofcontaminants. Direct ingestion refers to ingestion of the contaminant from the source area.Secondary ingestion refers to ingestion of the contaminant that deposits from the air onto thesurfaces of walls or equipment and is not restricted to the source area. The ingestion rates ofthese two mechanisms depend directly and indirectly, respectively, on the amount of removablecontaminant. Potential tritium exposures through the ingestion pathway are considered throughthe “removable fraction of the contaminant (fR),” “direct ingestion rate (ER),” “source lifetime(TR),” “deposition velocity (ud),” “resuspension rate (λR),” and “indirect ingestion rate (SER)”parameters. These parameters are used in Equations E.2, E.3, and B.3 of Appendixes E and B,respectively, to estimate the ingestion doses of tritium from direct ingestion, secondary ingestion,and the concentration of tritium on the walls or equipment due to deposition of airborne dustparticles. Section G.1.1 discusses parameters fR and TR. The other parameters, ER, ud, R, andSER, are discussed below.

The “direct ingestion rate” (ER) parameter is the same as that used for otherradionuclides. The removable contaminant is assumed to become airborne, be ingested directly,or drop to the floor and be swept away. If all the removable contaminant becomes airborne, thenthere would be no loose contaminant left for ingestion. Consequently, the value for thisparameter would be 0. This is generally the case for tritium in the form of HTO. For tritium in a

G-5

solid form that adsorbs to the source material and does not vaporize, the value for this parametershould be the same as that for other radionuclides.

Deposition of airborne tritium onto the surfaces of walls or equipment is considered forthe tritium in a solid form only. The values for ud, R, and SER for tritium released in solid formshould be the same as those for other radionuclides. Tritium that is released in a vapor form suchas HTO is assumed not to deposit (with a deposition velocity of 0) and will not cause secondaryingestion. When the deposition velocity is set to 0, the values of the resuspension rate andindirect ingestion rate will not affect the dose results.

G.2.3 Dermal Absorption

In the form of HTO, tritium can be absorbed easily by the human body through skincontact. To account for the potential dose from dermal absorption, the inhalation dose isincreased by 50%. The radiation doses listed for the inhalation pathway in the output text reportinclude the contribution from dermal absorption.

G.3 VOLUME SOURCES

The methodology used to assess exposures to tritium from a volume source is based onthe methodology used to assess exposures to other radionuclides but modified to consider therelease of tritium through vaporization. Currently, for volume sources, RESRAD-BUILD onlyconsiders the vaporization of HTO, the most common chemical form of tritium. Tritium in anyother chemical form is assumed to be released in solid form (absorbing or adsorbing to sourcematerial and not vaporizing); the release would occur through erosion only, which is consistentwith the approach for other radionuclides.

Because tritium emits only low-energy beta radiation, potential radiation exposureswould occur through inhalation, ingestion, and dermal absorption pathways. The methodologiesused to estimate the potential exposures are discussed below.

G.3.1 Inhalation

The potential release of tritium from a volume source would occur through erosion and, ifin the form of HTO, vaporization. To simplify the modeling of the vaporization mechanism,HTO molecules were assumed to behave exactly the same as the H2O molecules that also existin the source material (walls or equipment). On the basis of this assumption, the HTO moleculeswould follow the transport path of the H2O molecules. The release rate of tritium through theerosion mechanism is estimated on the basis of Equation D.1 in Appendix D. The release rate oftritium through the vaporization mechanism is estimated on the basis of a transport modeldiscussed in Section G.4.

G-6

Equation D.1 is used to estimate the release rate through erosion for other radionuclides.Because the release rate estimated is based on the assumption that all the contaminants adsorb tothe source material, Equation D.1 is modified to subtract the amount of tritium that has alreadybeen released through the vaporization mechanism. The underlying assumption is thatvaporization and diffusion through the source material occur much faster than erosion, so that theeroded source material would contain only the tritium that does not vaporize. An additional termis introduced into Equation D.1 and the equation becomes:

( ) ( )( )24

1000,10 relnsbssn

Si

ftCAEftI

−= ρ , (G.1)

where frel is the “fraction of tritium available for vaporization,” that is, “fraction of tritiated watermolecules available for vaporization (the free water molecules).” The factor (1�frel) is used toaccount for incorporation of the HTO and H2O molecules into the source entity, which prohibitsHTO and H2O from vaporization. The incorporation to the source entity is assumed to distributehomogeneously. When there is no incorporation to prohibit the vaporization of HTO or H2Omolecules, the value of frel is 1. For tritium in a chemical form other than HTO, that is assumedto be in a solid form, the value of frel should be set to 0.

Once the release rates of tritium from vaporization and erosion are estimated, the valuesare summed to give the total injection rate of tritium to the indoor air. This value is then used inthe indoor air quality model discussed in Appendix A to estimate the concentration of tritium ineach building compartment.

G.3.2 Ingestion

For the ingestion pathway, the radiation dose is estimated on the basis of Equation E.1(Appendix E), with additional multiplication by a factor of (1�frel), for direct ingestion andEquation E.3 for secondary ingestion. The factor (1�frel) is included in Equation E.1 becausevaporization occurs much faster than erosion, and the tritium that is released throughvaporization would not be available for ingestion. The value of frel would depend on thechemical form of tritium.

Secondary ingestion is considered mainly for tritium released in solid form. Therefore,for tritium released in vapor form (HTO vapor), the deposition velocity is usually set to 0. As forthe surface contamination source, the tritium concentration in the secondary surface sourceformed by the deposition of airborne solid particles is estimated with Equation E.3.

G.3.3 Dermal Absorption

The potential dermal absorption from the volume source is considered by increasing theinhalation dose by 50%, the same as for the surface source.

G-7

G.4 TRITIUM TRANSPORT MODEL

The tritium transport model incorporated into the RESRAD-BUILD code is used toestimate the injection rate of HTO molecules into the indoor air from vaporization. It wasadapted from the landfarming model developed by Thibodeaux and Hwang (1982) forconsidering volatilization of petroleum hydrocarbons from contaminated soils. The tritiumtransport model assumes that an amount of water containing HTO may somehow penetrate intothe building (walls or floor) or equipment material and be distributed homogeneously within adepth of h (cm) to hp (cm) (from the surface) within the material (shown in Figure G.1). Theregion where the water is distributed is called the wet zone; the dry zone is between the wet zoneand the interface of the indoor air and the contaminated material. To simplify the consideration,it is further assumed that the material properties of the dry zone and the wet zone are the same, asare the physical properties of the HTO and H2O molecules. Although the second assumption isnot necessarily valid, it would result in more conservative estimates of the potential exposures totritium because the release rate of HTO would be overestimated using the diffusivity andsaturated vapor pressure values of H2O. Since the HTO molecules would behave the same asH2O molecules, the use of the term water in the following discussion would actually mean watercontaining HTO, because any discussion about H2O molecules can also be applied to HTOmolecules.

In the void space of the contaminated material, free (not adsorbing to the source material)H2O molecules exist in liquid and vapor phases. Assuming the equilibrium condition, the watercontent in the vapor phase is saturated; that is, the partial pressure of water is equivalent to thesaturated vapor pressure of water. Because of the difference in the water vapor concentration inthe indoor air and in the void space of the wet zone, the water vapor molecule will diffuse fromthe region with the higher concentration to the region with the lower concentration; in this case,from the wet zone to the indoor air. With the water vapor molecules diffusing out, the H2Omolecules in the liquid phase will vaporize to sustain the equilibrium condition until no freewater molecules are available for vaporization. When the H2O molecules reach the surface of thesource material, they are released to the indoor air. The effects of surface characteristics are notconsidered in this model. It is assumed that the release rate of H2O molecules is controlled by thediffusion rate of H2O molecules through the dry zone, and that the H2O molecules at a smaller

FIGURE G.1 Schematic Representation of the Dry Zoneand Wet Zone Considered in the Tritium Transport Model

G-8

depth (closer to the dry zone) would vaporize earlier than those at a greater depth. As a result, atany time, the vaporization process would proceed by peeling the free H2O molecules from thetop of the wet zone. As time passes, the thickness of the dry zone (h) would increase, and thethickness of the wet zone (hp–h) would decrease (see Figure G.1).

According to Fick’s law, the diffusion rate of H2O molecules through the dry zone can beexpressed as:

,A thC C D

tq samb g,ge

water )(

)()(

−= (G.2)

where

qwater (t) = diffusion rate of H2O molecules across the surface of the sourcematerial per unit time at time t (g/s),

De = effective diffusion coefficient of H2O molecules in the source material(cm2/s),

Cg = concentration of H2O molecules in the vapor phase of the sourcematerial (g/cm3),

Cg,amb = concentration of water vapor in the indoor air, that is, the absolutehumidity in the indoor air (g/cm3),

h (t) = dry zone thickness in the source material at time t (cm), and

As = surface area of the contaminated zone (cm2).

Under the steady-state assumption, the vaporization rate from the wet zone is equivalent to thediffusion rate through the dry zone. Therefore,

,dt

tdh f C A = t q relsswater

)()( (G.3)

where

Cs = mass concentration of water in the wet zone (g/cm3) and

frel = fraction of free H2O molecules available for vaporization.

G-9

After combining Equations G.2 and G.3 and rearranging parameters, integration can beperformed on both sides of the equation to obtain Equation G.4:

,dh h f C = dt )C C( D rels

h

h

amb g,ge

t

0 s

∫∫ − (G.4)

where

hs = dry zone thickness at the beginning of time (t = 0) (cm).

Assuming that the values of Cg and Cg,amb are not functions of time, the dry zone thickness atany time t can be calculated by the following equation:

,f C

t )CC( D 2 +h = th

rels

ambg,ge2s

−)( (G.5)

where

t = elapsed time since the beginning of the vaporization process (s).

The parameter Cg� is used to represent (Cg – Cg,amb) to simplify the expression of equations:

Cg��= (Cg – Cg,amb) . (G.6)

Replacing parameter h in Equation G.2 with Equation G.5, the water diffusion rate at any time(t in seconds or t� in years) can be calculated as:

rels

timeges

sgewater

fC

ftCDh

ACDtq

′′+

′=′

2)(

2

, (G.7)

where

t� = elapsed time since the beginning of the vaporization process (yr)= t / ftime and

ftime = a conversion factor (3.1536 × 107 s/yr).

To estimate the release rate of tritium into the air, the value of qwater needs to bemultiplied by the activity concentration of tritium in water at time zero (AH3) and by a decayfactor. Equation G.8 is used to estimate the release rate of tritium into the indoor air:

qH3 (t�) = 3,600 AH3 e-λ t� qwater (t�), (G.8)

G-10

where

qH3 (t�) = release rate (diffusion rate) of tritium at time t� (pCi/h),

AH3(t�) = activity concentration of tritium in water at time zero (pCi/g),

� = radiological decay constant of tritium (1/yr), and

3,600 = a conversion factor of time (s/h).

The activity concentration of tritium in water, AH3, is related to the activity concentration oftritium in the contaminated zone, CH3, as shown in the following equation:

ρ

ρ+=

Wwater

bCA 1H3H3 , (G.9)

where

CH3 = activity concentration of tritium in the contaminated zone (pCi/g),

�water = density of water (g/cm3),

�b = bulk density of the porous material (g/cm3), and

W = moisture content in the contaminated zone (cm3/cm3).

The effective diffusion coefficient (De) used in Equation G.7 is dependent on the internalgeometry and porosity of the porous material (Currie 1960) and can be correlated to the airdiffusion coefficient (Di). According to the theoretical derivation by Millington and Quirk(1961), the correlation can be expressed as follows:

De = Di n4/3 , (G.10)

where n is the total porosity of the source material, and Di equals 0.2444 cm2/s.

The mass concentration of water in the contaminated zone (wet zone), Cs, can becalculated as:

Cs = W �water . (G.11)

The concentration of water vapor in the void space of the wet zone, Cg, is related to thesaturated vapor pressure of water, Psat, by the following equation:

TR

MWPC sat

g = , (G.12)

G-11

where

Psat = saturated vapor pressure of water (0.0245 atm),

MW = molecular weight of water (18 g/mol),

R = the gas constant [82 (atm × cm3)/(mol × K)], and

T = room temperature (298 K).

The amount of time required for the remaining free water in the wet zone to vaporize, td(t), is dependent on the thickness of the dry zone [h(t)] and the wet zone [hp – h(t)]. By the timeall the water molecules vaporize, h would be equivalent to hp. Therefore, the value of td can bederived for any time t with Equation G.5 after setting h to hp and hs to h. The resulting equationis:

( ) ( )ge

relpsd CD

fthhCtt

′−

=2

][ 22

, (G.13)

where td is expressed in seconds and can be converted to years by dividing by the timeconversion factor ftime.

RESRAD-BUILD estimates the average release rate of tritium over the exposureduration, ED. The exposure duration is always compared with the time required for theremaining free water to vaporize, td. When td is less than ED, the average release rate for thetime period td is estimated first, then normalized by the exposure duration, ED. If td is equivalentto or greater than ED, the average release rate over the exposure duration is calculated directlyand does not need normalization. The Newton-Cotes open integration method is used to estimatethe average release rate of tritium (Carnahan et al. 1977).

Once the average release rate of tritium is obtained, it can be added to the release rate oftritium from erosion. The sum of the release rates can then be used to estimate the tritiumconcentration in each building compartment.

The model described in this appendix neglects the isotopic effect and does not accountfor other mechanisms, such as adsorption and desorption, that may also affect the release rate ofHTO. Additional complexity in the model to account for these other mechanisms would make ananalytical solution impossible and would require introduction of new parameters with highdegrees of uncertainty. As a result, the tritium vaporization model in the RESRAD-BUILD codeshould be used for screening purposes only.

G-12

G.5 REFERENCES

Carnahan, B., et al., 1977, Applied Numerical Methods, John Wiley & Sons, Inc., New York,N.Y.

Currie, J.A., 1960, “Gaseous Diffusion in Porous Media. Part 2 — Dry Granular Materials,”British Journal of Applied Physics 11:318.

International Organization for Standardization, 1988, Evaluation of Surface Contamination.Part 2: Tritium Surface Contamination, ISO 7503-2:1988(E), Geneva, Switzerland.

Millington, R.J., and J.P. Quirk, 1961, “Permeability of Porous Solids,” Trans. Faraday Soc.57:1200–1207.

Thibodeaux, L.J., and S.T. Hwang, 1982, “Landfarming of Petroleum Wastes — Modeling theAir Emission Problem,” Journal of Environmental Progress 1:42.

U.S. Department of Energy, 1991, Recommended Tritium Surface Contamination ReleaseGuides, DOE/EH-0201T, Assistant Secretary for Environment, Safety, and Health, Washington,D.C., March.

H-1

APPENDIX H:

CALCULATION OF INTEGRATED DOSES

H-2

H-3

APPENDIX H:

CALCULATION OF INTEGRATED DOSES

The radiation doses calculated by the RESRAD-BUILD code are the total (integrated)doses incurred by the receptor over the entire exposure duration. The exposure duration is aninput parameter located under the Time Parameters section in the main input screen. Thecalculation of total dose for each individual pathway is accomplished by using the variousequations listed in Appendixes D through F. In the equations, average air concentrations —

[ )(tC ni ], average source concentrations — [ )(tC n

s , )(tC ndi , )(tC n

sV , )(tC nsL ], and average activities

— [ )(tQns and )(tC n

sP ] are used. For example, in Equation E.1:

DCF(t)CER FFED24(t)D ng

nsiin

n

il= , (H.1)

where (t)C ns is the average concentration of radionuclide n in the source material over the

exposure duration, (ED), starting at time t. Equation H.1 is identical to Equation E.1. Theaverage source concentration over the exposure duration used in Equation H.1 can be calculatedby the following equation:

∫

∫+

+

′

′′=

EDt

t

EDt

t

ns

ns

td

tdtC

tC

)(

)( , (H.2)

where )t(C ns ′ is the concentration of radionuclide n in the source material at any time t′, and t is

the start time for dose calculations. Similarly, average air concentrations, average sourceconcentrations, and average activities are calculated.

The integration of concentrations or activities from time t to t + ED is evaluatednumerically with Simpson's formula. The user can specify the maximum number of integrationpoints, up to 257, in the window brought up by pressing the Evaluation Times button in the maininput screen. The integration point is used to divide the exposure duration (from t to t + ED) intosmaller intervals and to obtain additional time points in addition to t and t + ED. Sourceconcentrations or total activities corresponding to t, t + ED, and the additional time points inbetween are calculated and multiplied by certain weighting factors according to Simpson’sformula. The sum of the weighted source concentrations or activities over all the time points isthen an estimate of the integrated source concentration or activity starting at time t over theexposure duration. This integrated source concentration or activity is then divided by theexposure duration to calculate the average source concentrations or activities as shown inEquation H.2.

H-4

The integration is initiated by using 1 and 2 integration points. The integration results arecompared with each other to see if they agree within 1%, that is, the differences are less than 1%.If they agree, no further integration calculation is needed, and the results obtained usingtwo integration points are reported. If they do not agree within 1%, additional integration withthree integration points is performed and the results are compared with those obtained usingtwo integration points. If the results agree within 1%, then the results obtained using threeintegration points are reported. Otherwise, further integration calculations are performed. Thenumber of integration points is then increased in the 2n + 1 sequence, starting with 2 (i.e., 2, 3, 5,9, 17, … 257). The calculations and comparison do not stop until either the user-specifiedmaximum integration point is reached or a better than 1% convergence is achieved. The lastcalculated integration results are reported.

I-1

APPENDIX I:

UNCERTAINTY ANALYSIS

I-2

I-3

APPENDIX I:

UNCERTAINTY ANALYSIS

Uncertainty or probabilistic analysis in RESRAD-BUILD is the computation of the totaluncertainty induced in the output (dose) as a result of either the uncertainty in or the probabilisticnature of the input parameters. This analysis helps determine the relative importance of theinputs in terms of their contributions to the total uncertainty. Also, the results of uncertaintyanalysis can be used as a basis for determining the cost-effectiveness of obtaining additionalinformation or data on input variables.

The RESRAD-BUILD code is designed to facilitate analysis of the effects of uncertaintyin or the probabilistic nature of input parameters in the RESRAD-BUILD model. A standardMonte Carlo method or a stratified Monte Carlo method can be applied to generate randomsamples of input variables. Each set of input variables is used to generate one set of outputresults. The results from applying all input samples are analyzed and presented in a statisticalformat in terms of the average value, standard deviation, minimum value, and maximum value.The cumulative probability distribution of the output is obtained and presented in a tabular formin terms of percentile values. Graphical presentations of the uncertainty results are also provided,including cumulative probability plots and scatter plots. Further analysis using regressionmethods can be performed to find the correlation of the resultant doses with the input variables.Partial correlation coefficients, partial rank correlation coefficients, standardized partialregression coefficients, and standardized partial ranked regression coefficients can be computedto provide tools for determining the relative importance of input variables in influencing theoutput. The scatter plots are also useful in determining the inputs that have a significant influenceon the output.

I.1 SAMPLING METHOD

Samples of the input variables are generated using an updated (1994) version of the Latinhypercube sampling (LHS) computer code (Iman and Shortencarier 1984). The uncertainty inputform of the RESRAD-BUILD user interface collects all the data necessary for the samplegeneration and prepares the input file for the LHS code. When the RESRAD-BUILD code isexecuted (run), the LHS code will be called if the user has requested a probabilistic/uncertaintyanalysis. Parameters for the sample generation include the initial seed value for the randomnumber generator, the number of observations (Nobs), the number of repetitions (Nrep), thesampling technique, the method of grouping the samples generated for the different variables, thetype of statistical distribution for each input variable, the parameters defining each of thedistributions, and any correlations between input variables.

Two sampling techniques are available LHS and simple random sampling (SRS). TheLHS technique is a constrained sampling scheme developed by McKay et al. (1979). It dividesthe distribution of each input variable into Nobs nonoverlapping regions of equal probability. Onesample value is obtained at random (using the current random seed) from each region on the

I-4

basis of the probability density function for that region. Each time a sample is obtained, a newrandom seed is also generated using the current random seed for use in the next region. Thesequence of random seeds generated in this manner can be reproduced if there is ever a need toregenerate the same set of samples. After a complete set of Nobs samples of oneprobabilistic/uncertain variable has been generated, the same procedure is repeated to generatethe samples for the next variable. The Monte Carlo sampling or SRS technique also obtains theNobs samples at random; however, it picks out each sample from the entire distribution using theprobability density function for the whole range of the variable. Report No. 100 of theInternational Atomic Energy Agency (IAEA) safety series (IAEA 1989) discusses the relativeadvantages of the two sampling techniques.

The Nobs samples generated for each probabilistic/uncertain variable must be combinedto produce Nobs sets of input variables. Two methods of grouping (or combining) are available— random grouping (RG) or correlated/uncorrelated grouping (CG). Under random grouping,the Nobs samples generated for each of the variables are combined randomly to produce Nobs sets

of inputs. For Nvar probabilistic/uncertain variables, there are (Nobs!)Nvar - 1 ways of combiningthe samples. It is possible that some pairs of variables may be correlated to some degree in therandomly selected grouping, especially if Nobs is not sufficiently larger than Nvar. In thecorrelated/uncorrelated grouping, the user specifies the degree of correlation between eachcorrelated variable by inputting the correlation coefficients between the ranks of the variables.The pairs of variables for which the degree of correlation is not specified are treated as beinguncorrelated, that is, having a zero correlation. The code checks whether the user-specified rankcorrelation matrix is positive definite and suggests an alternative rank correlation matrix ifnecessary. It then groups the samples so that the rank correlation matrix is as close as possible tothe one specified. Both matrices are in the Example1.un6 file, and the user should examine themto verify that the grouping is acceptable.

Iman and Helton (1985) suggest ways of choosing the number of samples for a givensituation. The minimum and maximum doses and risk vary with the number of samples chosen.The accuracies of the mean dose and of the dose values for a particular percentile depend on thenumber of samples and also on the percentile of interest in the latter case. The confidenceinterval or the (upper or lower) confidence limit of the mean can be determined from the resultsof a single set of samples. Distribution-free upper (u%, v%) statistical tolerance limits can becomputed by using the SRS technique according to the methodology in IAEA Report No. 100(IAEA 1989). For example, if the user is interested in the u% dose (e.g., 95 percentile dose), aspecific set of samples will yield an estimate of this u% dose. The user may want to find the v%upper confidence limit of this u% dose, which is called the upper (u%, v%) statistical tolerancelimit. That is, the user can be v% confident that the u% dose will not exceed the upper (u%, v%)statistical tolerance limit. The upper (u%, v%) statistical tolerance limit is the maximum dosepredicted by a sample of size n, where n is the smallest integer that satisfies the relation1 – (u%/100)n > v%/100. This applies to SRS. If LHS is used, a number of repetitions of thespecified number of samples can be performed in order to assess the range of the percentile doseof interest.

I-5

While the expression above can be used with simple random sampling, it is notapplicable for LHS. When LHS is used, it is necessary to repeat the analysis with Nrep differentsets of Nobs observations in order to assess the range of the percentile dose of interest. When theuser specifies Nrep repetitions, the LHS computer code will first generate the first set of Nobsobservations as described in the second paragraph of this section. The code then uses the lastseed it computed when generating the previous set of Nobs observations to generate the next setof Nobs observations. RESRAD-BUILD uses the Nrep sets of Nobs observations to produce Nrepsets of the desired output.

I.2 DISTRIBUTION PARAMETERS

The set of input variables for uncertainty analysis is chosen via the code’s interface. Eachvariable so chosen must have a probability distribution assigned to it and may be correlated withother input variables included in the uncertainty analysis. Thirty-four types of distribution areavailable in the LHS routine. These distribution types and distribution parameters aresummarized in Table I.1, at the end of this appendix.

I.3 UNCERTAINTY ANALYSIS RESULTS

The printable results of the uncertainty analysis are presented in the text fileRESBMC.RPT. The probabilistic inputs, their distributions, and the parameters of thedistributions are listed at the beginning of this file. This is followed by the statistics (mean,standard deviation, minimum, and maximum) of grand total dose, total dose from each source,total dose to each receptor, and total dose attributed to each source and receptor combination.These statistics are provided at each user time. The same statistics and the cumulative probabilityfor percentile values in steps of 5% are tabulated for the dose from each pathway and for thedose due each nuclide. These tables are provided for each user time, source, and receptorcombination. Tabulations of the correlation and regression coefficients of the doses (total dose,pathway doses, dose from each source, and the dose to each receptor) against the input variablesare provided for each repetition at the end of the report, at the user’s request. The input variablesare ranked according to their relative contribution to the overall uncertainty in these correlationand regression coefficient tables.

Tabular and graphical uncertainty results can be viewed in the interactive probabilisticoutput. Graphical results include scatter plots and cumulative density plots. Scatter plots can beviewed to observe any trends between each of the inputs and any of the following outputs: doseto each receptor via each or all pathways from each or all nuclides in each source at each usertime, and dose to each receptor via each or all pathways from all sources at each user time.Cumulative probability plots of these outputs are also available. Tabulations of the minimum,maximum, mean, standard deviation, and percentile values in steps of 5% are also available forthe same set of outputs. The 95% confidence range of these statistics is computed whenappropriate.

I-6

Detailed information pertinent to the samples processed is provided in a separate file,EXAMPLE1.UN6. This file contains the actual Latin hypercube samples for each observationand for each repetition. The file first provides the initial seed value of the random numbergenerator with which the code started, the number of variables selected for uncertainty analysis,the number of observations, and the number of repetitions. Next is a table for the input variablesand their distributions. The table provides the ranges of these variables rather than thedistribution parameters, which are provided in the file RESBMC.RPT. The input rank correlationmatrix is displayed if the user chooses to introduce some correlation among the input variables.Following that, tables for the actual observations and their ranks are provided. The rank ofobservations is applied in an ascending manner with rank 1 assigned to the lowest value. Thecorrelation of the input variables is then displayed for raw (actual) and for rank data. Thecorrelation matrix should be examined to ensure that the correlation introduced by the user isapplied and that undesired correlation is not significant. This information is provided in theEXAMPLE1.UN6 file for every repetition.

The primary results of the probabilistic runs are stored in files Uncout.asc andUncbuild.cdl. The probabilistic inputs used by the code are in file LHSBIN.DAT. The data inUncout.asc are used in the input-output correlation analysis, while Uncbuild.cdl is used togenerate the interactive output. These files may be accessed to analyze the complete set of rawoutput.

I.3.1 Description of Uncout.asc (ASCII)

Header lines:

Line 1: Blank.

Line 2: Uncertainty Output.

Line 3: NTime, NSrc, NRcp, and NPath: the number of evaluation times, the number ofsources, the number of receptors, and the number of exposure pathways.

Line 4: Headings for the columns of data. There is a column of data for each pathway,each source, and each receptor at every evaluation time. The number of columnsof data is NTime × (NPath + NSrc + NRcp).

Data lines:

The remaining Nobs × Nrep lines in this file: Data for each sample are in a single line. Thecolumns are described in line 4.

I-7

I.3.2 Description of Uncbuild.cdl (comma delimited ASCII )

Header lines:

Line 1: Nobs × Nrep, NTime, NRcp, NSrc, and Npath: the number of evaluation times,the number of receptors, the number of sources, and the number of pathways.

The following lines are repeated for each source:

Line i: NNucs(isrc): number of nuclides in source, isrc.

Lines ii through i+NNucs(isrc): names of nuclides in source, one to a line.

Data lines:

There are as many columns of data as there are pathways. The titles for the pathways are thesame as those listed in Uncout.asc, except that there is no total dose column.

The following NTime × NRcp × �NNucs(isrc) lines are repeated for each of the Nobs × Nrepuncertainty samples:

For each evaluation time a set of lines as follows,

For each receptor a set of lines as follows,

For each source a set of lines as follows, and

A line for each of the nuclides in the source.

I-8

TABLE I.1 Statistical Distributions Used in RESRAD-BUILD and Their Defining Parameters

Statistical Distribution Defining Parameters Description, Conditions, and Probability Density Function

NormalNormal

Normal-B

Mean (µ)Standard deviation (σ)

Value of the 0.1% (V0.001)Value of the 99.9% (V0.999)

There are two ways of specifying the “complete” normal distribution.The RESRAD code actually cuts off the lower and upper 0.1% tailsand samples between V0.001 and V0.999 in the latter case. Therelationship between the two sets of defining parameters follows:µ = (V0.999 + V0.001)/2 andσ = (V0.999 – V0.001)/2/3.09.

Conditions on inputs:

σ > 0, V0.001 < V0.999 .

Probability density function (pdf):

.x

exp)x(f

σµ−−

πσ=

2

2

1

2

1

Bounded Normal

Truncated Normal

Mean (µ)Standard deviation (σ)Minimum value (min)Maximum value (max)

Mean (µ)Standard deviation (σ)Lower quantile (Lq)Upper quantile (Uq)

Both parameters specify a normal distribution with the tails cut off.The lower cutoff is the minimum value or the lower quantile, and theupper cutoff is the maximum value or the upper quantile, which arerelated by min = VLq andmax = VUq.


min < max, Lq < Uq.

pdf:

.LqUq

xexp

)x(f−

σµ−−

πσ=

2

2

1

2

1

I-9

TABLE I.1 (Cont.)


Lognormal Lognormal

Lognormal-B

Lognormal-N

Mean (�)Error factor (EF)

Value of the 0.1% (V0.001)Value of the 99.9% (V0.999)

Mean (µ) of the underlying normal distributionStandard deviation (σ) of the underlyingnormal distribution

There are three ways of specifying the “complete” lognormaldistribution. The RESRAD code actually cuts off the lower and upper0.1% tails and samples between V0.001 and V0.999 in the second case.The relationship between the three sets of defining parameters follows:µ = (lnV0.999 + lnV0.001)/2 = lnM – σ2/2 andσ = (lnV0.999 – lnV0.001)/2/3.09 = 1nEF/1.645.The error factor (EF) is the ratio between the 95th percentile value andthe median (50th percentile) value. It is also the ratio between themedian value and the 5th percentile value.


M > 0, EF > 1, σ > 0, V0.001 < V0.999 .

pdf:

( ) .ln

2

1exp

2

12

−−=

σπσx

xxf

I-10

TABLE I.1 (Cont.)


Bounded Lognormal

Bounded Lognormal-N

Truncated Lognormal

Truncated Lognormal-N

Mean (�)Error factor (EF)Minimum value (min)Maximum value (max)

Mean (µ) of the underlying normal distributionStandard deviation (σ) of the underlyingnormal distributionMinimum value (min)Maximum value (max)

Mean (�)Error factor (EF)Lower quantile (Lq)Upper quantile (Uq)

Mean (µ) of the underlying normal distributionStandard deviation (σ) of the underlyingnormal distributionLower quantile (Lq)Upper quantile (Uq)

These four parameters specify a lognormal distribution with the tailscut off. The lower cutoff is the minimum value or the lower quantile,and the upper cutoff is the maximum value or the upper quantile, whichare related by min = VLq and max = VUq .


min < max, Lq < Uq .

pdf:

( ) .

ln

2

1exp

2

12

LqUq

x

xxf

−

−−

=σπσ

I-11

TABLE I.1 (Cont.)


Uniform Minimum value (min)Maximum value (max)


min < max

pdf:

f x( )max min

=−1 .

Loguniform Minimum value (min)Maximum value (max)


0 < min < max.

pdf:

f xx

( )( max min)

.=−

1

ln ln

Uniform* Number of subintervals (Nint)Limits of subintervals (Li) i = 0 to Nint

Number of observations in subinterval (Oint)

This is a collection of adjacent uniform distributions.


Nint > 1, Li�1 < Li , Oi > 0 , Nobs ii

Nint

==1

O∑ .

pdf:

f xi ( ) =− −

1

1L L

O

Ni i

i

obs

.

I-12

TABLE I.1 (Cont.)


Loguniform* Number of subintervals (Nint)Limits of subintervals (Li) i = 0 to Nint

Number of observations in subinterval (Oint)

This is a collection of adjacent loguniform distributions.


Nint > 1, 0 < LO, Li�1 < Li, 0i > 0, N Oobs ii

Nint

==1∑ .

pdf:

f (x)i =− −

1

x(ln ln )1L L

O

Ni i

i

obs

.

Continuous Linear Number of points (Npts)Values of points (Vi) i = 1 to Npts

cdf of points (cdfi) i = 1 to Npts

The cumulative distribution function (cdf) of a number of points isspecified, and the cdf of intermediate points is obtained by linearinterpolation.


Npts > 2, Vi < Vi + 1, cdf1 = 0, cdfNpts = 1.

pdf:

f xi ( ) =−−

−

−

cdf cdf

V Vi i

i i

1

1.

I-13

TABLE I.1 (Cont.)


Continuous Frequency Number of points (Npts)Values of points (Vi) i = 1 to Npts

Frequency of points (fi) i = 1 to Npts

The cdf of a number of points is first computed from the user-specifiedfrequencies. Then the cdf of intermediate points is obtained by linearinterpolation.

The cdf is computed from the frequencies as follows:

cdf1 = 0.

cdf cdff f f f

i ii i i i

i

N pts

= ÷−− −∑1

1 1

=2

++ +

2 2.


Npts > 2, Vi < Vi+1, fi > 0 .

pdf:

f xi ( ) =−−

−

−

cdf cdf

V Vi i

i i

1

1

Continuous Logarithmic Number of points (Npts)Values of points (Vi) i = 1 to Npts


The cdf of a number of points is specified, and the cdf of intermediatepoints is obtained by logarithmic interpolation.


N pts > 2 , 0 <V1 , V Vi i< +1 , cdf1 0= , cdf N pts= 1.

pdf:

f (x)cdf cdf

x( V Vii i

i i

=−−

−

−

1

1ln ln )

I-14

TAB LE I.1 (Cont.)


Triangular Minimum (min)Mode or most likely (mod)Maximum (max)


min < mod < max, min < max.

pdf:

( ) .modminmod

min

minmax

2 ≤−

−−

= xwhenx

xf

( ) .modmodmax

max

minmax

2 ≥−

−−

= xwhenx

xf

Pareto Alpha (α)Beta (β)

Make sure that the values entered for � and � correspond to thedefinition used for the pdf below.


� < 2, � > 0.

pdf:

f xx

( ) = +

α α

α

β1

when x > β.

Exponential

Exponential Lambda (λ) Conditions on inputs:

λ < 0.

pdf:

f(x) = λ exp(–λx).

I-15

TABLE I.1 (Cont.)


Bounded Exponential

Truncated Exponential

Lambda (λ)Minimum value (min)Maximum value (max)

Lambda (λ)Lower quantile (Lq)Upper quantile (Uq)

Three parameters specify an exponential distribution with the twoparameters defining the cut off. The lower cutoff is the minimum valueor the lower quantile, and the upper cutoff is the maximum value or theupper quantile, which are related by 1 – exp(-�min) = VLq and1-exp(-�max) = Vuq.


min < max, Lq < Uq.

pdf:

.LqUq

)xexp()x(f

−λ−λ

=

Weibull Alpha (α)Beta (β)



� > 0, � > 0.

pdf:

.a

xexp

x)x(f

β

−−α

ββ

α 1

I-16

TABLE I.1 (Cont.)


Inverse Gaussian Mean (µ)Lambda (λ)


µ > 0, λ > 0.

pdf:

( )f xx x

x( ) exp .= − −

λπ

λµ

µ2 23 2

2

Gamma Alpha (α)Beta (β)



α > 0, β > 0.

pdf:

f xx x

( )( ) exp( )

( )=

−−β β βα 1

Γ α.

Beta PQMinimum value (min)Maximum value (max)


min < max, 0.001 < P < 107, 0.001 < Q < 107.

pdf:

f (x)x x= + − − −

− − −

− −

+ −

( 1)!( min) (max )

( 1)!( 1)!(max min)

1 1

1

P Q

P Q

P Q

P Q.

I-17

TABLE I.1 (Cont.)

Statistical Distribution Defining Parameters Description, Conditions, and Probability Massa Function

Poisson Mean (�) Conditions on inputs:

� > 0.

Probability mass function (pmf):

p nn

n

( )exp( )

!=

−λ λ, where n = 0, 1, 2,... �.

Geometric Probability of success (p) Conditions on inputs:

0 < p < 1.

pmf:

p n p pn( ) ( )= − −1 1, where n = 0, 1, 2,... �.

Binomial Probability of success (p)Number of trials (N)


0 < p < 1, N > 1.

pmf:

p nN p p

n N n

n N n

( )! ( )

!( )!=

−−

−1, where n = 0, 1, 2,... N.

I-18

TABLE I.1 (Cont.)


Negative Binomial Probability of success (p)Number of successes sought (N)


0 < p < 1, N > 1.

pmf:

p nn p p

N n N

N n N

( )( )! ( )

( )!( )!=

− −− −

−1 1

1,

where n = N, N+1, .... �.

Hypergeometric Size of population (Npop)Sample size (Nsamp)Successes in population (Nsucc)

The second input has to be the smaller of Nsamp, Nsucc.The third input is the larger of the two.


Npop > Nsamp > 0, Npop > Nsucc > 0.

pmf:

p n

N

n

N N

N n

N

N

succ pop succ

samp

pop

samp

( ) ,=

−−

where M

m

M

m M m

=

−!

!( )!

and

n = max(0, Nsucc + Nsamp – Nop), ....min(Nsuccc, Nsamp)

I-19

TABLE I.1 (Cont.)


Discrete Cumulative Number of points (Npts)Values of points (Vi) i = 1 to Npts



Npts > 2, Vi < Vi + 1, cdf1 > 0, cdfNpts = 1.

pmf:

p(n) = cdfn – cdfn�1 .

Discrete Histogram Number of points (Npts)Values of points (Vi) i = 1 to Npts

Frequency of points (fi) i = 1 to Npts

cdf f fi i ii

N pts

= ∑/=1

.


Npts > 2, Vi < Vi+1, fi > 0 .

pmf:

p(n) = cdfn – cdfn�1 .

a Probability density function is for continuous distributions; mass function probability is for discrete distributions.

I-20

I.4 REFERENCES

IAEA, 1989, Evaluating the Reliability of Predictions Made Using Environmental TransferModels, International Atomic Energy Agency, Vienna, Austria, p. 106.

Iman, R.L., and J.C. Helton, 1985, A Comparison of Uncertainty and Sensitivity AnalysisTechniques for Computer Models, NUREG/CR-3904, SAND84-1461 RG, Sandia NationalLaboratories, Albuquerque, N.M., for U.S. Nuclear Regulatory Commission, Washington, D.C.,March.

Iman, R.L., and M.J. Shortencarier, 1984, A FORTRAN 77 Program and User’s Guide for theGeneration of Latin Hypercube and Random Samples for Use with Computer Models,NUREG/CR-3624, SAND83-2365 RG, Sandia National Laboratories, Albuquerque, N.M., forU.S. Nuclear Regulatory Commission, Washington, D.C., March.

McKay, M.D., et al., 1979, “A Comparison of Three Methods for Selecting Values of InputVariables in the Analysis of Output from a Computer Code,” Technometrics 21:239�245.

J-1

APPENDIX J:

PARAMETER DESCRIPTIONS

J-2

J-3

CONTENTS OF APPENDIX J

J.1 TIME PARAMETERS.................................................................................................... J-5J.1.1 Exposure Duration .............................................................................................. J-5J.1.2 Indoor Fraction.................................................................................................... J-6J.1.3 Number of Times for Calculation ....................................................................... J-12J.1.4 Time .................................................................................................................... J-13J.1.5 Maximum Time Integration Points ..................................................................... J-14J.1.6 References ........................................................................................................... J-15

J.2 BUILDING PARAMETERS .......................................................................................... J-16J.2.1 Number of Rooms............................................................................................... J-16J.2.2 Deposition Velocity............................................................................................. J-18J.2.3 Resuspension Rate .............................................................................................. J-26J.2.4 Room Height ....................................................................................................... J-36J.2.5 Room Area .......................................................................................................... J-38J.2.6 Air Exchange Rate .............................................................................................. J-40J.2.7 Flow Rate between Rooms.................................................................................. J-47J.2.8 Outdoor Inflow and Outflow............................................................................... J-48J.2.9 References ........................................................................................................... J-49

J.3 RECEPTOR PARAMETERS......................................................................................... J-56J.3.1 Number of Receptors .......................................................................................... J-56J.3.2 Receptor Room.................................................................................................... J-58J.3.3 Receptor Location ............................................................................................... J-59J.3.4 Receptor Time Fraction....................................................................................... J-60J.3.5 Receptor Breathing/Inhalation Rate .................................................................... J-61J.3.6 Indirect Ingestion Rate ........................................................................................ J-66J.3.7 References ........................................................................................................... J-69

J.4 SOURCE PARAMETERS ............................................................................................. J-71J.4.1 Number of Sources.............................................................................................. J-71J.4.2 Source Room....................................................................................................... J-72J.4.3 Source Type......................................................................................................... J-73J.4.4 Source Direction.................................................................................................. J-75J.4.5 Source Location................................................................................................... J-76J.4.6 Source Length/Area............................................................................................. J-77J.4.7 Air Release Fraction............................................................................................ J-78J.4.8 Direct Ingestion Rate........................................................................................... J-80J.4.9 Removable Fraction ............................................................................................ J-81J.4.10 Source Lifetime................................................................................................... J-85J.4.11 Radon Release Fraction....................................................................................... J-90J.4.12 Radionuclide Concentration/Activity.................................................................. J-91J.4.13 Number of Regions in Volume Source ............................................................... J-93

J-4

CONTENTS OF APPENDIX J (Cont.)

J.4.14 Contaminated Region.......................................................................................... J-94J.4.15 Source Region Thickness .................................................................................... J-95J.4.16 Source Density .................................................................................................... J-97J.4.17 Source Erosion Rate............................................................................................ J-101J.4.18 Source Porosity ................................................................................................... J-104J.4.19 Radon Effective Diffusion Coefficient ............................................................... J-107J.4.20 Radon Emanation Fraction.................................................................................. J-110J.4.21 Source Material ................................................................................................... J-113J.4.22 References ........................................................................................................... J-114

J.5 SHIELDING PARAMETERS ........................................................................................ J-119J.5.1 Shielding Thickness ............................................................................................ J-119J.5.2 Shielding Density ................................................................................................ J-121J.5.3 Shielding Material ............................................................................................... J-124J.5.4 References ........................................................................................................... J-125

J.6 TRITIUM MODEL PARAMETERS.............................................................................. J-126J.6.1 Dry Zone Thickness ............................................................................................ J-126J.6.2 Wet + Dry Zone Thickness ................................................................................. J-127J.6.3 Volumetric Water Content .................................................................................. J-130J.6.4 Water Fraction Available for Vaporization......................................................... J-131J.6.5 Humidity ............................................................................................................. J-134J.6.6 References ........................................................................................................... J-137

J.7 RADIOLOGICAL UNITS .............................................................................................. J-138J.7.1 Acitivity Units ..................................................................................................... J-138J.7.2 Dose Units........................................................................................................... J-139

J-5

J.1 TIME PARAMETERS

J.1.1 Exposure Duration

Definition: The exposure duration is the total length of time considered by the dose assessment,including intervals during which receptors may be absent from the building (see Section J.1.2 onthe indoor fraction) or a contaminated indoor location (see Section J.3.4 on the receptor timefraction). The exposure duration is used to calculate the amount of time at each receptor locationas time at receptor location = exposure duration × indoor fraction × receptor time fraction.

Parameter Name: TTIME Units: Days (d) Range: > 0

Deterministic Analysis Default Value: 365

Probabilistic Analysis Default Distribution: None assigned

Window: Time Parameters

Discussion: The total dose depends on the scenario considered. For chronic scenarios such asbuilding occupancy, a period of 365 days typically would be selected to assess an annual dose.Total doses over periods exceeding 1 year may be calculated by entering a longer exposureduration. For short-term exposures, such as building renovation, the estimated time in days fromthe beginning to end of the exposure should be entered. If site-specific time estimates forbuilding renovation are not available, a value of 90 days may be used (Kennedy and Strenge1992).

J-6

J.1.2 Indoor Fraction

Definition: The indoor fraction is the fraction of the exposure duration (see Section J.1.1 onexposure duration) spent by one or more receptors inside a building. The indoor fraction is usedin the exposure calculations to calculate the amount of time spent at each receptor location.Actual exposure times at each location are estimated by multiplying the exposure duration by theindoor fraction and the fraction of time at the receptor location. This parameter applies to allindoor receptor locations.

Parameter Name: FTIN Units: Unitless Range: ≥ 0

Deterministic Analysis Default Value: 0.5

Probabilistic Analysis Default Distribution: User-defined continuous with linear interpolationDefining Values for Distribution:See Table J.1 for the input values.

Window: Time Parameters

Discussion: The fraction of time a receptor spends inside a building may range from 0 to 1. Thisnumber will depend on the anticipated occupancy of the building. This parameter should takeinto account anticipated occupancy rates based on current practices. For example, an officeworker may be assumed to spend 2,000 hours per year working inside the building, with thesehours distributed uniformly through out the year. The resulting indoor fraction is the ratio of2,000 hours to 8,760 hours in one year (365 days × 24 hours/day), or 0.23. A different total timemay be used for a renovation scenario (e.g., 90 days, of which 500 hours are spent working). Thisdifference in exposure duration, however, would not affect the indoor fraction. Residentialoccupancy scenarios might result in higher indoor fractions than would occupational scenarios.

With the exposure duration given in units of days, the indoor fraction is represented bythe fraction an individual spends indoors at work in the case of occupational exposure. Beyeleret al. (1998) examined records from the Bureau of Labor Statistics (BLS) concerning the hours atwork for persons employed in the agricultural and nonagricultural industries (BLS 1996). Thedistribution given in Table J.2 was based on the assumption that full-time nonagriculturalworkers spent 35 hours or more a week at work. However, some workers may spend some timeoutside.

The U.S. Environmental Protection Agency’s (EPA’s) Exposure Factors Handbook (EPA1997) contains a comprehensive review of human activity patterns, including time spent at work.That review extracts data for time spent at work from the most complete and current study onactivity patterns (Tsang and Klepeis 1996). Table J.3 summarizes a number of distributions,including distributions for time spent indoors at unspecified work locations in a

J-7

plant/factory/warehouse. The distribution for full-time workers in the plant/factory/warehousecategory is expected to be a good representation for workers in a building occupancy scenarioand is the default distribution for the indoor fraction for RESRAD-BUILD. For perspective, the50th percentile value for this distribution, 0.365, corresponds to an 8.76-hour work day. Thecumulative distribution function for the indoor fraction is shown in Figure J.1.

The EPA’s comprehensive review of human activity patterns (EPA 1997) also containsstatistics on the amount of time spent indoors at a residence. Table J.4 summarizes the relevantsubset of distributions provided in the Exposure Factors Handbook (EPA 1997) for this timefraction. These distributions can be used when evaluating the potential use of a building for aresidential setting. It can be seen that the indoor fraction is substantially lower for anoccupational setting (50th percentile range of 0.194 to 0.365 in Table J.3) than for a residentialsetting (50th percentile range of 0.625 to 0.729 in Table J.4).

J-8

TABLE J.1 CumulativeDistribution Functionfor the Indoor Fraction

CumulativeProbability

DefaultOccupationalDistribution

0 0.0030.05 0.03470.25 0.3060.50 0.3650.75 0.4030.90 0.4690.95 0.5000.98 0.5420.99 0.5941.0 0.692

TABLE J.2 Relative Frequency of Hours Workedby Persons Working 35 Hours or Moreper Week

Assuming a 5-DayWork Week

Hours Workedper Weeka

RelativeFrequencya

Hoursper Day

Fractionof Day

35–39 9.96 � 10-2 7–7.8 0.32539–41 4.81 � 10-1 7.8–8.2 0.34241–48 1.59 � 10-1 8.5–9.6 0.40049–59 1.53 � 10-1 9.8–11.8 0.49260–65 1.08 � 10-1 12–13 0.542

a Source: Beyeler et al. (1998).

J-9

TABLE J.3 Statistics for Fraction of Time Spent Indoors at Worka

Percentile

CategoryPopulation

Group Nb Min Max 5 25 50 75 90 95 98 99

Fraction per Day Indoors at a Plant/Factory/WarehouseAll 383 0.001 0.692 0.021 0.243 0.354 0.394 0.465 0.490 0.535 0.594Gender Male 271 0.001 0.692 0.021 0.253 0.358 0.399 0.469 0.500 0.542 0.604Gender Female 112 0.003 0.569 0.010 0.218 0.354 0.385 0.417 0.469 0.490 0.500Age (years) 18-64 353 0.003 0.692 0.021 0.267 0.361 0.396 0.465 0.490 0.535 0.594Employment Full-Time 333 0.003 0.692 0.035 0.306 0.365 0.403 0.469 0.500 0.542 0.594

Fraction per Day Spent Indoors at Work (unspecified)All 137 0.003 0.680 0.010 0.125 0.306 0.385 0.460 0.563 0.653 0.667Gender Male 96 0.007 0.680 0.014 0.170 0.328 0.415 0.531 0.583 0.667 0.680Gender Female 41 0.003 0.542 0.010 0.063 0.194 0.344 0.382 0.410 0.542 0.542Age (years) 18-64 121 0.003 0.680 0.010 0.167 0.313 0.389 0.458 0.551 0.590 0.667Employment Full-Time 97 0.007 0.680 0.010 0.208 0.333 0.406 0.479 0.566 0.667 0.680

a Derived from cumulative minutes per day spent indoors as listed in EPA (1997).

b Number of subjects in the survey.

J-10

FIGURE J.1 Indoor Fraction Cumulative Distribution Function for an Occupational Setting

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80

Indoor Fraction

F(x)

J-11

TABLE J.4 Statistics for Fraction of Time Spent Indoors in a Residencea

Percentile

CategoryPopulation

Group Nb Min. Max. 5 25 50 75 90 95 98 99

Fraction per Day Indoors in a Residence (all rooms)All 9,343 0.006 1 0.399 0.552 0.684 0.858 0.969 1 1 1Gender Male 4,269 0.006 1 0.375 0.521 0.625 0.806 0.938 0.993 1 1Gender Female 5,070 0.021 1 0.431 0.583 0.729 0.889 0.986 1 1 1Age (years) 18-64 6,022 0.006 1 0.375 0.521 0.625 0.809 0.938 0.992 1 1

a Derived from cumulative minutes per day spent indoors as listed in EPA (1997).

b Number of subjects in the survey.

J-12

J.1.3 Number of Times for Calculation

Definition: This parameter represents the number of user-defined discrete exposure periods forwhich the dose calculations are performed. This parameter allows the user to assess the dose atdifferent times (years) to evaluate any time-dependent effects, such as source removal or erosionand radioactive decay and ingrowth (see Sections J.1.1 and J.1.4 on exposure duration and time,respectively). The exposure period starting at the initial time (Time = 0) is automaticallycalculated and reported.

Parameter Name: NTIME Units: Unitless Range: 1 to 10

Default Value: 1

Window: Time Parameters → Evaluation Times

Discussion: The use of this parameter is the same whether the analysis being performed isdeterministic or probabilistic. The value for the number of times for calculation entered by theuser is an integer ranging from 1 to 10. For simple problems in which ingrowth or source lossduring the assessment period is not a factor, setting the number of times for calculation to 1 maybe sufficient. The number of times for calculation should be based on estimated or actualexposure durations for the selected scenario. The run time of the code is directly proportional tothe selected number of times for calculation.

J-13

J.1.4 Time

Definition: This parameter refers to the beginning time(s) of the exposure duration for whichdose calculations are performed.

Parameter Name: DOSE_TIME Units: Years Range: ≥ 0 to 100,000

Default Value: 1

Window: Time Parameters → Evaluation Times

Discussion: The use of this parameter is the same whether the analysis being performed isdeterministic or probabilistic. Up to nine user-specified times (in years) may be selected asstarting points for the dose calculations. The code will always calculate the dose at time zero.These times can be integer years or fractions of years. The dose is calculated over the specifiedexposure duration (see Section J.1.1 on exposure duration) in days following each assessmenttime entered. For example, if the exposure duration time is 365 days and the user selects times 1and 10 years, the code will calculate doses incurred during the first (time zero is alwayscalculated), second, and eleventh year. For short-lived radionuclides, or when significantingrowth occurs during the assessment period, the user may divide the assessment time intoequally spaced time intervals to account for changing dose rates. For example, an actualassessment time of 90 days may be divided into three equal intervals of 30 days each. Theexposure duration would then be entered as 30 days, and the user would enter the number oftimes for calculation (see Section J.1.3 on number of times for calculation) as 3, settingcalculation times at t = 0, 0.083, and 0.167 years. The code would then calculate the dose overthe first, second, and third 30-day periods, respectively. The total dose to each receptor would bethe sum of the receptor dose at each calculation time.

The dose assessment times should be based on estimated or actual exposure durations forthe selected scenarios. These times should be consistent with actual, proposed, or hypotheticalfuture use scenarios for the building. For example, if the postulated scenario is buildingoccupancy, the selected times should not go beyond the time at which the source may undergosignificant changes (such as during building renovation) and certainly not beyond the anticipatedlifetime of the building.

The user may change the times by editing the parameter fields or by dragging the clockicons across the time horizon chart. The times need not be arranged in chronological order.However, the user may rearrange the times by clicking on the reorder button, and also does soautomatically upon exiting the input window. To avoid overlapping dose calculations, the usershould check that the exposure duration does not exceed the interval between times forcalculations.

J-14

J.1.5 Maximum Time Integration Points

Definition: This parameter refers to the maximum number of points used in integrating the doserate over the exposure duration.

Parameter Name: POINT Units: Unitless Range: 1, 2, 3, 5, 9, 17, 33,65, 129, 257

Default Value: 17

Window: Time Parameters → Maximum Time Integration Points

Discussion: The dose reported at any evaluation time is obtained by numerically integrating thedose rate over the exposure duration at each receptor location. The user can specify the maximumnumber of points to be used for the time integration. The code will use as many time integrationpoints as is necessary to achieve the present convergence criteria, subject to the maximum points(limits) specified.

The user can select 1, 2, 3, 5, 9, 17, 33, 65, 129, or 257 as the number of points tocalculate the time-integrated dose. If the user selects 1, then the instantaneous dose at the user-specified time is calculated. The use of integration points is discussed in Appendix H.

J-15

J.1.6 References

Beyeler, W.E., et al., 1998, Review of Parameter Data for the NUREG/CR-5512 BuildingOccupancy Scenario and Probability Distributions for the DandD Parameter Analysis, letterreport prepared by Sandia National Laboratories, Albuquerque, N.M., for U.S. NuclearRegulatory Commission, Washington, D.C., Jan.

BLS: See Bureau of Labor Statistics.

Bureau of Labor Statistics, 1996, “Annual Household Data,” in Employment and Earnings,Vol. 43, No. 1, Bureau of Labor Statistics, Washington, D.C., Jan.

EPA: See U.S. Environmental Protection Agency.

Kennedy, W.E., and Strenge, D.L., 1992, Residual Radioactive Contamination fromDecommissioning; A Technical Basis for Translating Contamination Levels to Annual TotalEffective Dose Equivalent, NUREG/CR-5512, PNL 7994, Vol. 1, prepared by Pacific NorthwestLaboratory, Richland, Wash., for U.S. Nuclear Regulatory Commission, Washington, D.C., Oct.

Tsang, A.M., and N.E. Klepeis, 1996, Results Tables from a Detailed Analysis of the NationalHuman Activity Pattern Survey (NHAPS) Response, draft report prepared by Lockheed Martin forU.S. Environmental Protection Agency.

U.S. Environmental Protection Agency, 1997, Exposure Factors Handbook, Update to ExposureFactors Handbook, EPA/600/8-89/043 — May 1989, EPA/600/P-95/002Fa,b&c, National Centerfor Environmental Assessment, Office of Research and Development, U.S. EnvironmentalProtection Agency, Washington, D.C., Aug.

J-16

J.2 BUILDING PARAMETERS

J.2.1 Number of Rooms

Definition: The number of rooms is the number of distinct airflow regions in the part of thebuilding being modeled. This parameter could represent the number of rooms, the number oflevels, or the number of parts of a space where air is hindered from being quickly mixed. Thisparameter affects only the pathways that depend on airflow. It does not influence the externalpathway. In fact, many more rooms can be modeled in the external pathway by appropriate use oflocations and shielding.

Parameter Name: NROOM Units: Unitless Range: 1, 2, or 3

Default Value: 1

Window: Building Parameters

Discussion: Probabilistic input is not available for this parameter. The number of rooms can beset from one (to represent complete instantaneous air mixing of the internal volume beingmodeled) to three (to represent three separate airflow regions with well-characterized airexchange patterns). The three rooms might be three levels of a house, two levels of a buildingplus the stairwell, or similar combinations. The more rooms there are in a problem, the morecomplicated the airflow specification will be (see Sections J2.6, J.2.7, and J.2.8 on the airexchange rate, net flow, and outdoor inflow, respectively). Figure J.2 shows various roomconfiguration examples. The number of airflow input parameters strongly depends on the numberof rooms parameter.

J-17

3-Room House2-Room House1-Room Warehouse

2-Story House 2-Story Building with2 Rooms on the First Floor

2-Story Housewith Basement

(No air exchangebetween basement

and outdoors.)

3-Story House

CYA10101

indicates air exchange

FIGURE J.2 Examples of Potential Discrete Airflow Regimes in a Building

J-18

,V

dAdud =λ

J.2.2 Deposition Velocity

Definition: This parameter represents the indoor deposition velocity of contaminant particles inthe building air.

Parameter Name: UD Units: m/s Range: ≥ 0


Probabilistic Analysis Default Distribution: LoguniformDefining Values for Distribution:Minimum: 2.7 × 10-6 Maximum: 2.7 × 10-3


Discussion: The buildup of radionuclides on surfaces as a result of deposition of airborneradioactive materials is an important process in several exposure pathways. Deposited beta- andgamma-emitting radionuclides contribute to exposure from external radiation. Depositedradioactive materials also can become airborne because of mechanical disturbances or airflow(see Section J.2.3 on resuspension rate) and serve as a source of radionuclide inhalation oradditional contamination. The same deposition velocity is used for all radionuclides in thecalculations. If this assumption violates the conditions being modeled (e.g., if some nuclides arein the form of particulates and others are in the form of vapor, two different cases should beanalyzed, one for particulates and another for the vapors. The appropriate deposition velocityshould be specified for each case.

The deposition velocity characterizes the rate at which particles in the indoor air deposit�� d, of particles in indoor air due to deposition is often expressed as:

(J.2.2-1)

where

ud = deposition velocity,

Ad = surface area available for deposition, and

V = volume of air.

J-19

For indoor deposition, the deposition velocity depends on particle and room properties. Importantparticle properties include diameter, density, and shape; room properties include air viscosity anddensity, turbulence, thermal gradients, and surface geometry.

Nazaroff and Cass (1989) have developed a relationship for the indoor depositionvelocity of particulates as a function of particle size. Such theoretical calculations are not likelyto produce satisfactory results because of lack of knowledge about near-surface flow conditions(Nazaroff et al. 1993), but they can provide insight into the general trend of deposition velocityas a function of particle size. Figure J.3 presents an idealized representation of depositionvelocity on a floor as a function of particle size on the basis of the methodology in Nazaroff andCass (1989). A similar trend is observed for deposition of particles outdoors (Sehmel 1980).

Because deposition velocities depend on particle size, it is expected that the probabilitydensity function distribution of deposition velocities is dependent on the particle sizedistribution. The particle size distribution in the atmosphere typically exhibits three modes�� !��into two modes — nuclei and accumulation. The nuclei mode (particles approximately 0.005 to"�� #�� only a few percent of the total mass of airborne particles (Seinfeld and Pandis 1998). Nucleimode particles are formed from condensation of atmospheric gases, such as combustionproducts. Depletion of nuclei mode particles occurs primarily through coagulation with larger�� $��"�� for a large portion of the aerosol mass. Accumulation mode particles are formed throughcoagulation of particles in the nuclei mode and through condensation of gases onto smallerparticles. Because removal mechanisms are not as efficient for this size range, particles tend toaccumulate (hence the term “accumulation mode”). Coarse particles (diameters greater than2.5� �� %�� mode particles are formed primarily from mechanicalprocesses. Other sources of coarse particles include windblown dust and plant particles.

Each of the three particle size modes can be well characterized by lognormal distributions(John 1993). In using the means and standard deviations from Whitby and Sverdrup (1980),Figure J.4 demonstrates the trimodal nature of the particle size distributions commonly found.Similar distributions are expected for indoor air concentrations, with the exception of someindoor source contributions, because, as discussed in Yu et al. (2000), the building shell has been� �&�� #�� '��"� ��

A broad probability density function distribution is expected for the deposition velocitywhen comparing the trend in deposition velocity with the distribution of particles by size(Figures J.3 and J.4, respectively) and taking into consideration the variability of each.Experimental estimates provide support for such an assumption, as shown in Tables J.5 throughJ.7. In addition, Vette et al. (2001) and Mosley et al. (2001) both observed a comparableU-shaped curve, as suggested by Figure J.3, when plotting particle size against indoor depositionrate (decay rate, Equation J.2.2-1), which is directly proportional to the deposition velocity.However, numerical information was not presented in either study for further evaluation here.

J-20

Deposition rate data over a broad particle size range were presented by Wallace et al. (1997) andAbt et al. (2000). These data, as converted to deposition velocity in Table J.5, provide furthersupporting evidence. A similar trend for deposition velocity as a function of particle size, assuggested by Figure J.3, is also observed for deposition of particles outdoors (Sehmel 1980).

In conjunction with particle size and mass, a small difference in the local air handlingsystem (such as changes due to climate or season) can easily cause a shift in deposition velocitybecause deposition is dependent on local airflow patterns (Nazaroff and Cass 1989). Because thedeposition velocity input in RESRAD-BUILD is used for all particle sizes and species under apotential range of airflow conditions, a loguniform distribution is recommended when usingprobabilistic input, with minimum and maximum values of 2.7 × 10-6 m/s and 2.7 × 10-3 m/s,respectively, as found in Tables J.5 through J.7. This distribution is shown in Figure J.5.

J-21

FIGURE J.3 Idealized Representation of Indoor Particle Deposition Velocity

FIGURE J.4 Trimodal Nature of Aerosol Particle Size Distribution

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

1.00E-03 1.00E-02 1.00E-01 1.00E+00 1.00E+01 1.00E+02

Particle Diameter (�m)

dN

/d l

n n

Average background

Urban average

Background+local sources

1.E-06

1.E-05

1.E-04

1.E-03

1.E-02

1.E-01

1.E+00

1.00E-03 1.00E-02 1.00E-01 1.00E+00 1.00E+01 1.00E+02

Particle Diameter (�m)

Dep

osit

ion

Vel

ocit

y (m

/s)

J-22

TABLE J.5 Estimated Indoor Deposition Velocities by Particle Size

Particle Size� ��

DepositionVelocity (m/s) Comments Reference

0.71 1.7 × 10-5 7Be with natural air exchange Lang (1995)1.4 1.3 × 10-5

2.8 6.7 × 10-5

0.71 1.33 × 10-4 7Be with forced air exchange1.4 2.66 × 10-4

2.8 3.88 × 10-4

1–2 1.7 × 10-4 Data set 1 (different sample dates using Thatcher2–3 3.7 × 10-4 sulfur hexafluoride [SF6] tracer) and Layton3–4 5.1 × 10-4 (1995)4–6 1.1 × 10-3

1–2 1.9 × 10-4 Data set 22–3 5.0 × 10-4

3–4 5.6 × 10-4

4–6 1.2 × 10-3

1–5 3.1 × 10-4 Data set 35–10 9.1 × 10-4

10–25 1.6 × 10-3

>25 2.7 × 10-3

0.07 1.72 × 10-5 Estimates based on data in Offermann et al. Nazaroff0.10 2.7 × 10-6 (1985) from cigarette combustion and Cass0.12 3.8 × 10-6 (1989)0.17 3.8 × 10-6

0.22 4.7 × 10-6

0.26 8.9 × 10-6

0.35 8.2 × 10-6

0.44 8.7 × 10-6

0.56 9.8 × 10-6

0.72 1.51 × 10-5

0.91 1.3 × 10-4

<2.5 3 × 10-5 and 3 × 10-5 Sulfate ion particulates at two locations Sinclair et al.(1985)

2.5–15 1 × 10-2 and 2 × 10-3 Calcium ion particulates at two locations

0.3 1.4 × 10-4 Estimated from decay rates by usingEq. J.2.2-1 and assuming a residence with an8-ft (2.438-m) ceiling height and alldeposition to the floor. Area/volume =1/2.438 1/m.

Wallace et al.(1997)

J-23

TABLE J.5 (Cont.)

Particle Size� ��

DepositionVelocity (m/s) Comments Reference

0.5 2.5 × 10-4

1 4.0 × 10-4

2.5 5.2 × 10-4

5 1.0 × 10-3

>10 1.9 × 10-3

0.02–0.1 7.3 × 10-4 Particles generated during cooking activities. Abt et al.0.1–0.2 7.5 × 10-4 Estimated from decay rates by using

Eq. J.2.2-1 and assuming a residence with an8-ft (2.438-m) ceiling height and all depositionto the floor. Area/volume = 1/2.438 1/m.

(2000)

0.2–0.3 5.4 × 10-4

0.3–0.4 5.1 × 10-4

0.4–0.5 4.74 × 10-4

0.7–1 7.3 × 10-4

1–2 6.6 × 10-4

2–3 8.0 × 10-4

3–4 1.0 × 10-3

4–5 1.2 × 10-3

5–6 1.3 × 10-3

6–10 2.1 × 10-3

J-24

TABLE J.6 Estimated Deposition Velocities byParticle Size in Residences with and withoutFurniture

Average Deposition Velocity (m/s)Particle

Size ( �� Without Furniture With Furniture

0.5 6.1 � 10-5 8.2 � 10-5

2.5 1.33 � 10-4 1.73 � 10-4

3.0 1.37 � 10-4 2.25 � 10-4

4.5 2.88 � 10-4 2.88 � 10-4

5.5 3.04 � 10-4 3.24 � 10-4

Source: Fogh et al. (1997).

TABLE J.7 Estimated IndoorDeposition Velocities for VariousRadionuclides

IsotopeMean Deposition

Velocity (m/s)

Cs-137 6.4 � 10-5

Cs-134 6.2 � 10-5

I-131 (particulate) 1.1 � 10-4

Be-7 7.1 � 10-5

Ru-103 2.0 � 10-4

Ru-106 1.7 � 10-4

Ce-141 3.1 � 10-4

Ce-144 3.9 � 10-4

Zr-95 5.8 � 10-4

Nb-95 1.9 � 10-4

Source: Roed and Cannell (1987).

J-25

FIGURE J.5 Indoor Deposition Velocity Probability Distribution

1.E+00

1.E+01

1.E+02

1.E+03

1.E+04

1.E+05

1.E-06 1.E-05 1.E-04 1.E-03 1.E-02

Indoor Deposition Velocity (m/s)

f(x)

Loguniform Distribution

Minimum = 2.7 � 10-6 m/s

Maximum = 2.7 � 10-3 m/s

J-26

J.2.3 Resuspension Rate

Definition: The resuspension rate (indoor) represents the rate at which material deposited oninterior surfaces is resuspended into the indoor air per unit time. Resuspension is the result ofairflow or a mechanical disturbance, such as walking across a surface or sweeping.

Parameter Name: DKSUS Units: s-1 Range: ≥ 0

Deterministic Analysis Default Value: 5 × 10-7

Probabilistic Analysis Default Distribution: LoguniformDefining Values for Distribution:Minimum: 2.5 × 10-11 Maximum: 1.3 × 10-5


Discussion: Indoor resuspension of contamination can lead to external exposure and internalexposure via inhalation. The resuspension rate is the fraction of deposited particles resuspendedper unit time. Factors that can affect resuspension include the type of disturbance (airflow vs.mechanical), the intensity of the disturbance, the type of surface, particle size distribution, andphysical and chemical characteristics of the particles.

Relatively little work has been conducted in measuring or estimating indoor resuspensionrates. The most recent work by Thatcher and Layton (1995) monitored an sulfur hexafluoride(SF6) tracer in a residential setting under varying conditions. Table J.8 gives the results based onparticle size. These results demonstrate that the larger particle sizes are more susceptible toresuspension. Other studies investigating the characteristics and dynamics of indoor dustbehavior have shown that the primary source of larger particle sizes in indoor air is resuspension(Wallace et al. 1997; Vette et al. 2001). Thus, it is important to note, as has been done previously(Jones and Pond 1967), that a large fraction of resuspended material is nonrespirable.

Nonrespirable material is material that cannot be inhaled directly into the lungs. Largerparticulates, greater than approximately 2.5 µm in diameter, cannot reach the deep respiratorytract where gas exchange occurs. This material becomes trapped in the nasal passages or upperrespiratory tract, where it can dissolve and be absorbed into the blood or cleared by mechanicalaction (swallowing) into the gastrointestinal tract or exhaled. Current radiological inhalation doseconversion factors (e.g., those presented in Eckerman et al. 1999) are based on a particle size ofapproximately 1 µm in diameter. Risks from smaller or larger particles could be lower or higher,depending on the radionuclide and its speciation. Currently, not enough information is availableto provide this type of radiological risk information on the basis of particle size. Neither is thereenough information to provide estimates of resuspension rate according to particle size. Thus, thecurrent resuspension rate model is particle size independent; however, the assigned distribution is

J-27

influenced by the available data on varying particle sizes. The latest available resuspension rateinformation is discussed below.

Earlier studies of indoor resuspension of radioactive contamination reported the extent ofresuspension in terms of a resuspension factor (Rf), that is, the ratio of airborne contamination tothe amount deposited on surfaces. The following derivation provides an approximate conversionbetween the resuspension factor and the resuspension rate. When conservation of mass isassumed, the total change in the amount of airborne particulate material in a room (the left sideof Equation J.2.3-1) is equal to an increase due to the amount resuspended, a decrease due todepositing material, and a decrease due to ventilation (terms 1 through 3, respectively, on theright side of Equation J.2.3-1).

= Cs × A × �r � CA × A × ud – CA × V × n , (J.2.3-1)

where

CA = contaminant air concentration,

CS = contaminant surface concentration,

λr = resuspension rate,

V = A × H (the room volume),

A = contaminated surface area (assumed to be the floor where depositionoccurs),

H = room height,

ud = deposition velocity, and

n = number of air changes per unit time.

When both sides of the equation are divided by the room volume and when equilibriumconditions (dCA/dt = 0) are assumed, the following is obtained:

.nCH

uC

HC A

dA

rS 0=×−−

λ(J.2.3-2)

VdC

dtA

J-28

Separation of the surface and air terms gives:

.

+= n

H

uC

HC d

Ar

sλ

(J.2.3-3)

The resuspension factor is the ratio of the air to surface concentration, as shown inEquation J.2.3-4. From this, the relationship between the resuspension rate and the resuspensionfactor is derived (see Equation J.2.3-5).

.HnuC

CR

d

r

S

Af ×+

==λ

(J.2.3-4)

( ) .HnuR dfr ×+=λ (J.2.3-5)

Table J.8 gives some indoor resuspension rates and the corresponding resuspensionfactors as determined by using Equation J.2.3-5. Only those references with the additionalrequisite data (room height and air exchange rate) were used to estimate the resuspension ratefrom the resuspension factor. Because the deposition velocity was not measured in each case, theminimum and maximum values from the deposition velocity distribution (Section J.2.2) wereused to provide a resuspension rate range for each resuspension factor. Data for the resuspensionrates were provided in the case of Thatcher and Layton (1995), from which correspondingresuspension factors were derived by using deposition velocities supplied in that reference. Healy(1971) previously studied the correlation of the resuspension factor with the resuspension rate.Sansone (1987) and Beyeler et al. (1999) reviewed the earlier work in the context of resuspensionfactors rather than rates. Table J.9 summarizes previous work in the area of resuspension factorsnot addressed in Table J.8.

A number of factors (ventilation, physical activity/location, contaminated particle/floorcharacteristics, contamination source, and housekeeping practices) must be considered inselecting an appropriate distribution for the resuspension rate from the data discussed above.Many of the studies from which resuspension factors were derived or presented do not includeenough information on room volume, contaminated surface area, and/or the ventilation rate inorder to make a rough estimate of the resuspension rate by using the relationship inEquation J.2.3-1. The magnitude of the resuspension factor, however, can be roughly correlatedwith the conditions under which it was obtained and can be compared with resuspension factorsthat have corresponding resuspension rates, as shown in Table J.8.

Ventilation rates in commercial buildings that might fall under the light industrialclassification for the building scenario are expected to be near 1 air change per hour (seeSection J.2.6). Those studies conducted with no ventilation are expected to overestimate theresuspension factor because some removal of the air contamination would occur under normaloperating conditions. In contrast, those studies with excessive ventilation might underestimate

J-29

the reported resuspension factor because more air contamination would be removed under theseconditions than under normal operating conditions.

Physical activity is an important factor in the resuspension of particulate matter. Adramatic example was presented by Wallace et al. (1997), who monitored air particleconcentrations during a study of an occupied townhouse. Coarse particle (5–10 µm) airconcentrations were shown to be orders of magnitude higher during the periods of time that theoccupants were not sleeping or away. Even working in front of a computer had a large impact oncoarse particle (> 2.5 µm) resuspension (Wallace et al. 1997). Other studies have also indicatedthat a major source of larger particles (> 1.0 µm) in indoor air is resuspension (Vette et al. 2001).Thus, those resuspension factor studies with high levels of physical activity are not representativeof what an average individual might experience in the course of a working day. At the otherextreme, studies conducted with no physical activity are also nonrepresentative and mightunderestimate the value of the resuspension factor.

The location of the surface-contaminated area(s) will affect the estimated resuspensionfactor and resuspension rate. Deposited material on the floor in a high-traffic area is much morelikely to be resuspended than deposited material on equipment, walls, or seldom-traversed areas.The same is also true for “fixed” residual contamination in remediated areas. The larger theconstantly disturbed area, the larger the resuspension factor. Thus, this consideration is closelyallied with physical activity, as previously discussed.

The likelihood of particle resuspension is related to its adherence to the surface.Contamination remaining after remediation is expected to be relatively “fixed,” that is, hard toremove because it is tightly bound (e.g., chemically bonded) or deep within microscopicdepressions of the surface. In the latter case, it is actually the result of the inability of mechanicalaction to contact the contamination when a rough surface is encountered. In contrast, depositedmaterial is generally loosely bound and relatively easily resuspended. Thus, the primary source ofthe contamination (“fixed” or deposited) must also be taken into consideration when determiningthe resuspension factor or resuspension rate for use in risk assessment.

Normal housekeeping operations, such as dusting. sweeping, mopping, and vacuuming, ina light industrial environment will minimize potential risks to building occupants fromresuspension of contaminated materials during normal working hours. Risks to the cleaning staffwill be elevated, but only for short periods of time. These operations reduce the buildup ofcontaminated material from deposition and further reduce any residual “fixed” contamination.Thus, those buildings with more frequent cleaning schedules are expected to have lowerresuspension factors/rates than those sporadically cleaned, because the more loosely boundmaterial from deposition is maintained at lower levels.

The RESRAD-BUILD input parameters, such as the source lifetime, removable fraction,and air release fraction, are used to control the amount of contaminated material that becomesavailable within the building from residual contamination. In turn, the resuspension rate inRESRAD-BUILD must account for resuspension of the resultant deposited contamination. In

J-30

DandD, however, the resuspension factor is the only input that accounts for airbornecontamination and, therefore, must be more concerned with the source (residual contamination),which is not as easily removed as is deposited material. Thus, the input distribution inRESRAD-BUILD for the resuspension rate covers a wider range of equivalent values than theinput distribution for the resuspension factor in the DandD code (McFadden et al. 2001). In thelatter, values should be limited to “fixed” contamination in order to avoid violating thecontamination mass balance and overestimating the inhalation exposure.

A loguniform distribution is suggested to represent the resuspension rate in RESRAD-BUILD because of the limited data available and the wide range of estimated values. The widerange in the estimated values can be attributed primarily to differences in particle size and indoorhuman activity levels. To represent an occupational setting, the lowest value involving any typeof activity in Table J.8 was chosen, 2.5 × 10-11 s-1. Similarly, the largest value in Table J.8,1.3 × 10-5 s-1, was chosen as the maximum value for the distribution. Figure J.6 shows theprobability density function selected for the indoor resuspension rate.

J-31

TABLE J.8 Indoor Resuspension Rates

Resuspension Rate (1/s)a

Minimum MaximumResuspension

Factor (m-1) Conditions Reference Comments

7.7 × 10-7 1.1 × 10-6 1.2 × 10-4 4–6 people walking Brunskill (1967) Change room, 1 – 3% removed bysmears, 50% by water wash.

5.1 × 10-10

1.1 × 10-10

2.5 × 10-11

1.9 × 10-9

5.1 × 10-7

1.1 × 10-7

2.5 × 10-8

1.9 × 10-6

1.9 × 10-4

3.9 × 10-5

9.4 × 10-6

7.1 × 10-4

Vigorous work, including sweeping (ZnS)Vigorous walking (ZnS)Collecting contaminated samples (ZnS)Light sweeping with fans on for circulation (CuO)

Fish et al. (1967) Measurements of ZnS and CuO tracers.

3.3 × 10-8 2.2 × 10-7 4 × 10-6

to2 × 10-5

Pu Ikezawa et al. (1980) Cleanup following accidental failure of aPu glove box.

1.9 × 10-10

9.5 × 10-8

4.8 × 10-7

1.9 × 10-10

9.5 × 10-9

4.8 × 10-8

2.5 × 10-10

1.2 × 10-7

6.1 × 10-7

2.5 × 10-10

1.2 × 10-8

6.1 × 10-8

2 × 10-8

1 × 10-5

5 × 10-5

2 × 10-8

1 × 10-6

5 × 10-6

Plutonium oxide, no movement14 steps/min36 steps/minPlutonium nitrate, no movement14 steps/min36 steps/min

Jones and Pond (1967) Contamination applied in solution andallowed to dry.

4.2 × 10-8

3.3 × 10-8

3.7 × 10-6

1.1 × 10-5

4.8 × 10-8

3.9 × 10-8

4.3 × 10-6

1.3 × 10-5

2.5 × 10-6

2.0 × 10-6

2.2 × 10-4

6.8 × 10-4

Alpha, no work performedBeta, no work performedAlpha, floors scrubbed with cottonBeta, floors scrubbed with cotton

Khvostov andKostiakov (1969)

Investigation of a “hot” laboratory.

2.4 × 10-9 2.4 × 10-6 9.0 × 10-4 Ba35SO4 Shapiro (1970) Membrane with Ba35SO4 ignited andcombustion products deposited on floor;maximum value of subsequentmeasurements made while banging onfloor.

1.4 × 10-6

3.8 × 10-7

3.2 × 10-6

2.1 × 10-6

2.0 × 10-6

5.4 × 10-7

4.5 × 10-6

2.9 × 10-4

2.2 × 10-4

5.9 × 10-5

4.9 × 10-4

3.2 × 10-5

Personal air samplersArea air samplersPersonal air samplersArea air samplers

Tagg (1966) 100 steps/min, contaminated floor;100 steps/min, contaminated clothing.

J-32

TABLE J.8 (Cont.)

Resuspension Rate (1/s)a

Minimum MaximumResuspension

Factor (m-1) Conditions Reference Comments

2.8 × 10-10

1.2 × 10-10

5.0 × 10-9

2.3 × 10-8

1.1 × 10-7

9.4 × 10-9

NAb

NAb

NAb

NAb

NAb

NAb

1.4 × 10-6

6.0 × 10-7

9.4 × 10-6

2.0 × 10-5

6.1 × 10-5

3.2 × 10-6

0.3–0.5 µm particles0.5–1 µm particles1–5 µm particles5–10 µm particles10–25 µm particles> 25 µm particles

Thatcher and Layton(1995)

Estimated for residence with fourresidents performing “normal” activities.Assumed air exchange rate of 0.3 h-1.

a Estimated from the resuspension factor using Equation J.2.3-5 and minimum and maximum values for the deposition velocity from Section J.2.2.

b Not applicable. Resuspension factors were estimated from resuspension rates for Thatcher and Layton (1995).

J-33

TABLE J.9 Resuspension Factors from Previous Studies

Resuspension Factor

(m-1)a Conditions Reference Comments

1.8 × 10-6

4.3 × 10-5

I-131Active work in open spaceActive work in confined, unventilated space

Chamberlain andStanbury (1951)

I-131 labeled brick and plaster dust (bulk ofdust <1 µm), as reported in Sansone (1987).

2.5 – 19 × 10-5 UF4 powder Bailey and Rohr (1953) Normal operations at a uranium processingplant.

1 × 10-9 – 4.2 × 10-6

7 × 10-8 – 4 × 10-5

Uranium, total surface activity usingratemeter, larger if removableactivity values used.

Ra, total surface activity usingratemeter, larger if removableactivity values used.

Eisenbud et al. (1954) Estimated from surface and airborne activity at5 uranium processing plants.

Estimated from surface and airborne activity at10 radium plants

4 × 10-5 “Dusty operations” Barnes (1959) As reported in McKenzie et al. (1998).

5 × 10-4

3 × 10-5

U compounds0.5-h samples8-h samples

Becher (1959) As reported in Sansone (1987). Wipes used tomeasure surface activity

0.2 – 5.9 × 10-5

0.5 – 14 × 10-4

UOre sampling plantUranium reduction plant

Utnage (1959) As reported in Sansone (1987).

1.5 × 10-2

5 – 12 × 10-3

7.9 × 10-3

9.3 × 10-3

2 × 10-2

Be and compoundsLoading/unloading Be blocksCleaning Be blocksBe cyclotron target preparationBe compound synthesisWarehouse inventory

Hyatt et al. (1959) Resuspension factor as estimated by Sansone(1987). Surface contamination measured bywipe; maximum values for wipe and airconcentration used.

0.4 – 26 × 10-5

0.8 – 14 × 10-4

U compounds8-h air samples10-min air samples

Schulz and Becher(1963)

As estimated by Sansone (1987), measurementsfrom operating UF6 manufacturing plant,surface contamination measured by wipes.

1.0 × 10-4

1.3 × 10-4

1.45 × 10-4

1.0 × 10-4

1.35 × 10-3

9.7 × 10-3

UUndisturbedFans onFans on with movement

PuUndisturbedFans onFans on with movement

Glauberman et al.(1967)

As reported in Sansone(1987), operatinguranium processing plant, abandoned preciousmetals.

Recovery plant (Pu contamination), surfacecontamination measured with smears.

J-34

TABLE J.9 (Cont.)

Resuspension

Factor (m-1)a Conditions Reference Comments

4.2 × 10-4

1.0 × 10-2

BeTwo men sweeping vigorouslySweeping after vacuuming

Mitchell and Eutsler(1967)

As reported in Sansone(1987). Unventilatedstoreroom with wood floor, smears used forsurface contamination.

<=1.7 × 10-7

4.7 – 7.5 × 10-6

<=0.7 × 10-7

1.0 – 1.7 × 10-5

UO2In ethanol, undisturbedIn ethanol, 60 steps/minPowder, undisturbedPowder, 60 steps/min

Cortissone et al. (1968) As reported in Sansone (1987).

1.2 – 5.3 × 10-3

2.0 – 4.2 × 10-3

ChrysotileContaminated lab coathandling contaminated materials

Carter (1970) As reported in Sansone (1987), surfacecontamination measured by vacuuming.

1.2 × 10-4

3.3 × 10-4Sr applied in solutionCo applied in solution

Gorodinsky et al.(1972)

As reported in Sansone (1987), after 1 h inwind tunnel; steel, painted steel, stainlesssteel, vinyl plastic, and organic glass surfaceshad essentially the same results.

0.2 – 13 × 10-6

0.01 – 1.5 × 10-6

0.3 – 10 × 10-6

0.08 – 1.5 × 10-6

Be (aqueous suspension applied)Fan onFan offAmmonium fluoroberyllate(aqueous solution applied)Fan onFan off

Kovygin (1974) As reported in Sansone (1987).From polyvinyl chloride surface, 1.8 m/sairflow with fan on.

4 × 10-5 Pu under unspecified conditions Wrixon et al. (1979) As estimated in Sansone (1987), using datafrom the reference.

5.7 × 10-4 Workplace for I-125 immunoassaystudies

Dunn and Dunscombe(1981)

Surface contamination measured using wipeswith 70% isopropyl alcohol.

5.5 × 10-8 to 1.1 × 10-7

Radioactive particulates Ruhter and Zurliene(1988)

Activity in Three Mile Island auxiliarybuilding during cleanup after accident.

4.25 × 10-7

7.79 × 10-6

8.97 × 10-7

U; surface contamination measuredusing wipes, three 1-year averages

Spangler (1998) U storage area at operating uranium fuelfabrication plant.

1.7 × 10-7

4.2 × 10-8

Primarily Co-60 and Cs-137during decommissioningshutdown mode

Nardi (1999) No forced air ventilation, measurements at a“pump repair” facility.

J-35

Resuspension Rate (s-1)

FIGURE J.6 Indoor Resuspension Rate Probability Density Function

1.E+00

1.E+01

1.E+02

1.E+03

1.E+04

1.E+05

1.E+06

1.E+07

1.E+08

1.E+09

1.E+10

1.E-12 1.E-11 1.E-10 1.E-09 1.E-08 1.E-07 1.E-06 1.E-05 1.E-04 1.E-03

-1

f(x)


Minimum = 2.5 � 10-11 s-1

Maximum = 1.3 � 10-5 s-1

J-36

J.2.4 Room Height

Definition: The room height is the distance between the floor and the ceiling of a specific roomin the building.

Parameter Name: H Units: m Range: > 0


Probabilistic Analysis Default Distribution: TriangularDefining Values for Distribution:Minimum: 2.4 Maximum: 9.1 Most likely: 3.7

Window: Building Parameters → Airflow (room details)

Discussion: The room height is used in determining the mixing volume of each distinct airflowvolume (room) and the equilibrium of resuspension and deposition. It is used in conjunction withthe area of the room and the airflow rates to compute the building air exchange rate and the roomair exchange rate. By its nature, the airflow volume could also represent the space within a crawlspace under a house (about 1 m in height) or the stairwell in a multistory building (e.g., 3 mheight per floor). The height is set for each defined room in the analysis and should be consistentwith the definition of that room.

Over half the new single-family homes constructed annually have room heights of 2.4 m(8 ft), as shown in Table J.10. The 2.4-m (8-ft) height is considered to be typical of residentialhousing (EPA 1997). Minimum room heights of 2.1 m (7 ft) below beams and girders arerequired by the Council of American Building Officials, with a ceiling height of not less than2.3 m (7.5 ft) for half of the required area (National Association of Home Builders [NAHB]1998). The U.S. Department of Housing and Urban Development requires a minimum ceilingheight of not less than 2.1 m (7 ft) for at least half of the floor area and 1.9 m (6 ft 4 in.) underducts and beams.

No comprehensive study of room height in commercial buildings exists. Room height canvary within the same occupational setting as well as between industries. Room height may alsovary according to climate (because of energy efficiency considerations). A typical room height incommercial buildings is 3.7 m (12 ft) (EPA 1997). A minimum of 2.4 m (8 ft) is found in smallerrooms, such as those used for individual offices or conference rooms. Larger room heights arefound in warehousing (shipping/receiving) operations, which may have room heights of up toapproximately 9.1 m (30 ft). Thus, for an occupational scenario, such as light industry, a defaulttriangular distribution for the room height is suggested, with a most likely value of 3.7 m andminimum and maximum values of 2.4 and 9.1 m, respectively. This distribution is a rough

J-37

generalization, and site-specific data should be used when available. The probability densityfunction is shown in Figure J.7.

TABLE J.10 Room Height in New Conventional andManufactured Homes, 1996

Room Height(m) [ft]

ConventionalHomes (first floor),

(percent of total)Manufactured Homes

(percent of total)

� 2.1 [� 7] 0.1 48.22.3 [7.5] 1.6 37.42.4 [8.0] 57.8 5.12.6 [8.5] 0.8 1.52.7 [9.0] 24.2 7.7

> 2.7 [> 9] 15.5 �

Source: NAHB (1998).

FIGURE J.7 Room Height Probability Density Function

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0 1 2 3 4 5 6 7 8 9 10 11

Room Height (m)

f(x)

Triangular DistributionMinimum = 2.4 mMaximum = 9.1 mMost Likely = 3.7 m

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J.2.5 Room Area

Definition: This parameter represents the floor area of a specific room in the building.

Parameter Name: AREA Units: m2 Range: > 0


Probabilistic Analysis Default Distribution: TriangularDefining Values for Distribution:Minimum: 3 Maximum: 900 Most likely: 36


Discussion: The room area is used in determining the mixing volume of each distinct airflowvolume (room) and the equilibrium of resuspension and deposition. It is used in conjunction withthe height of the room and the airflow rates to compute the building air exchange rate and theroom air exchange rate. By its nature, the airflow volume could represent the space within asmall storage area (e.g., about 1 m2) or a warehouse (e.g., thousands of m2). The area is set foreach defined room in the analysis and should be consistent with the definition of that room.

Studies concerning room size distribution are not available. An arbitrary distribution hasbeen selected as a default for use in application of RESRAD-BUILD to commercial buildings.Site-specific distributions or deterministic values should be used if available. A triangulardistribution is used to represent the room area. A minimum value of 3 m2 (approximate roomdimensions of 1.5 × 2 m) was chosen to represent such areas as utility rooms or storage closets ina commercial environment. A maximum value of 900 m2 (slightly less than 10,000 ft2) waschosen to represent larger areas that would correspond to the area of rooms housing suchfunctions as light industrial assembly lines, small to intermediate warehouse operations, or largeassembly halls. However, office space is generally required in support of such larger operations.Such a requirement skews the room size distribution toward smaller room area, which suggeststhat a uniform distribution between the minimum and maximum areas is not appropriate. Thechoice of a most likely value for a triangular distribution was arbitrary and attempted to accountfor this observation. A most likely value of 36 m2 (390 ft2) was chosen. This value lies abovewhat might be expected for the area for a single-occupant office room (approximately 12 m2,3 m × 4 m) and is in the range of what might be expected for a multioccupant office room.Figure J.8 presents the probability density function suggested for the room area.

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FIGURE J.8 Probability Density Function for Room Area

0.0000

0.0005

0.0010

0.0015

0.0020

0.0025

0 200 400 600 800 1000

Room Area (m2)

f(x)

Triangular Distribution

Minimum = 3 m2

Maximum = 900 m2

Most Likely = 36 m2

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J.2.6 Air Exchange Rate

Definition: The air exchange (or ventilation) rate for a building or a room is the total volume ofair in the building or room replaced by outside air per unit of time. For example, a building (orroom) with a ventilation rate of 1 per hour (1/h) has its air replaced once each hour on average.

Parameter Name: LAMBDAT (building); LINPUT (room) Units: 1/h Range: > 0

Deterministic Analysis Default Value: 0.8/h (building air exchange rate for one-room model)

Probabilistic Analysis Default Distribution: lognormal-n (probabilistic input is only availablefor LAMBDAT, the building air exchange rate)Defining Values for Distribution:Underlying mean value: 0.4187 Lower quantile value: 0.001Standard deviation: 0.88 Upper quantile value: 0.999


Discussion: The building air exchange rate is input by the user for a one-room building. It iscomputed by using the heights and the areas of the rooms and by using the airflow rates into andout of the rooms for two-or three-room buildings. In RESRAD-BUILD, the building isconceptualized as a structure composed of up to three rooms. Air exchange is assumed betweenrooms 1 and 2 and rooms 2 and 3 but not between rooms 1 and 3. All rooms can exchange airwith the outdoor atmosphere. The air exchange rate parameter is used in the air quality model.For the one-room model, the air exchange rate for the building and that for the room are the samevalue; this value is an input required by the code. For the two-room and three-room models,inflow from outside and the flow between the rooms are required. The room air exchange rate fortwo- or three-room buildings is computed by using the height and the area of the room and theairflow rates into and out of the room. The room air exchange rate strongly depends on thenumber of rooms, inflow, outflow, and net flow within the rooms. The full flow of air can becalculated only if the parameters satisfy certain conditions that guarantee a positive exchange ofair between the rooms.

Air exchange involves three processes: (1) infiltration, which is air leakage throughrandom cracks, interstices, and other unintentional openings in the building; (2) naturalventilation, which is airflow through open windows, doors, and other designed openings in thebuilding; and (3) forced, or mechanical, ventilation, which is controlled air movement driven byfans.

The average infiltration rate for a building can be expressed as the number of air changesper hour or air exchange rate (h-1). A single building can have a wide range of air exchange ratesboth in the short- and long-term, depending on environmental conditions at a particular time

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(e.g., seasonal/diurnal temperature, pressure, and ambient wind speed and direction); otherfactors include opening and closing of doors and windows, building type, construction, age, andventilation system. A number of studies have attempted to characterize building air exchangerates under different environmental conditions for buildings with different leakagecharacteristics.

Measurement of the ventilation rate in a building (or room) can be accomplished directlyby first injecting a tracer gas, SF6, into the house and then, after a mixing time, using an infraredanalyzer to measure the gas concentration as a function of time. The ventilation rate is equal tothe rate of decay of the tracer concentration (Nero 1988).

A passive measurement technique that is available releases a gaseous tracer from a smallsource at a constant rate inside the building. A collector monitor, consisting of a diffusive tubeand an absorber, measures the average concentration during the time the system is in operation.The measured concentration is proportional to the inverse of the ventilation rate. Furtherreferences for these ventilation rate measurement techniques, as well as some predictivequantitative models, can be found in Nazaroff et al. (1988), Nero (1988), and Sherman (1990).

The air exchange rate can be found by dividing the room air-volume exchange rate by theroom volume. These parameters can be estimated if the building specifications are known(e.g., the air-volume exchange rate in a forced-air heating/cooling system can be estimated bymultiplying the vent area and the velocity of forced air). The air exchange rate of the entirebuilding is the total volume of air going out of the building per unit of time divided by the totalvolume of the building.

A comprehensive study of residential ventilation rates was published by Pandian et al.(1993). To evaluate the distribution of ventilation rates of a large population of homes in theUnited States, the researchers analyzed a Brookhaven National Laboratory (BNL) databaseconsisting of more than 4,000 residential perfluorocarbon tracer (PFT) measurements fromapproximately 100 individual studies. Table J.11 presents summary statistics from that study onair exchange rates in the United States and regionally. Pandian et al. (1993) also analyzed thedata by season and by the number of levels with the homes. They concluded that exchange ratesare higher in the Southwest than in the Northeast and Northwest; summer ventilation rates aremuch higher than winter and fall rates; and multilevel residences have higher air exchange ratesthan single-level residences. The authors present both arithmetic and geometric means andstandard deviations, as well as percentile distributions.

Murray and Burmaster (1995) also used the data compiled by BNL using the PFTtechnique to estimate univariate parametric probability distributions for air exchange rates forresidential structures in the United States. The analysis was characterized by four key points: theuse of data for 2,844 households; a four-region breakdown based on heating degree days;estimation of lognormal distributions as well as provision of empirical (frequency) distributions;and provision of these distributions for all of the data. The authors summarized distributions forsubsets of the data defined by climate region and season. The coldest region (region 1) was

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defined as having 7,000 or more heating degree days, the colder region (region 2) as having5,500 to 6,999 degree days, the warmer region (region 3) as having 2,500 to 5,499 degree days,and the warmest region (region 4) as having fewer than 2,500 degree days. The months ofDecember, January, and February were defined as season 1; March, April, and May as season 2;June, July, and August as season 3; and September, October, and November as season 4. Theauthors concluded that the air exchange rate was well fit by lognormal distributions for smallsamples sizes except in a few cases. The mean and standard deviations are listed in Table J.11.The authors recommended that the empirical or lognormal distribution may be used in indoor airmodels or as input variables for probabilistic health risk assessments.

In a study sponsored by the EPA (Koontz and Rector [1995]), a similar data set asanalyzed by Murray and Burmaster (1995) was used. However, an effort was made tocompensate for the nonrandom nature of the data by weighting results to account for each state’sshare of occupied housing units. As shown in Table J.11, the results of Murray and Burmaster(1995) are similar to those of Koontz and Rector (1995).

Air exchange rates from other representative residential studies are also summarized inTable J.11. The type of distribution can vary, depending on the type of study. For example, asurvey of various housing types by Grimsrud et al. (1983) demonstrated that houses generallyhave air exchange rates that fall in a lognormal distribution between 0.1 and approximately 3 h-1,with most clustered in the 0.25 to 0.75 range; however, some older (“leaky”) houses, includinglow-income housing, had infiltration rates exceeding 3 h-1. In contrast, Lipschutz et al. (1981)obtained measurements of air infiltration into 12 energy-efficient houses in Oregon by using atracer gas decay analysis. A narrow range of values was found (0.08 to 0.27 h-1), reflecting theextremely “tight” building construction and ventilation systems installed in the houses.

Doyle et al. (1984) measured air exchange rates in 58 weatherized houses during a 4- to5-month period during both winter and summer sampling periods. The houses were located inFargo, North Dakota; Colorado Springs, Colorado; Portland, Maine; and Charleston, NorthCarolina. The investigators determined the geometric means and geometric standard deviationsfor air exchange rates for each city and for the entire sample. Because of the relatively smallnumber of measurements in each city, conclusions about the geographic distribution of airexchange rates are limited. However, combining the data for the cities provides an overalllognormal distribution of 0.8 ±1.8 h-1 (ranging from 0.2 to 2.3 h-1), which appears to encompassmost air exchange rates determined in other studies.

Studies on the air exchange rates of large commercial buildings have been much morelimited. Table J.12 lists results from some studies on commercial buildings. It can be seen thatthese values are relatively close to those for residential construction. Although the primaryoutside air source for large buildings is the mechanical ventilation system, infiltration is theprimary outside air source for residential homes (American Society of Heating, Refrigeration,and Air-Conditioning Engineers [ASHRAE] 1997). In either case, a continuous supply of outsideair is required to dilute and eventually remove indoor contaminants. Thus, the air exchangerequirements are expected to be similar for both residential and commercial construction.

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However, differences in local airflow and temperature, as well as air exchange, may be requiredto maintain workers’ comfort according to their activity level.

Turk et al. (1987) examined the outdoor exchange rates of 38 buildings in the PacificNorthwest. The buildings included schools, libraries, and office buildings in mild and harshclimates measured during different seasons of the year. Results are shown in Table J.12. Thearithmetic mean and standard deviation are 1.52 h-1 and 0.873, respectively. Although this set ofdata is limited, the mean falls between the arithmetic means determined Pandian et al. (1993) andMurray and Burmaster (1995), 1.99 and 0.76 h-1, respectively, for residential air exchange rates.The air exchange data from Persily and Grot (1985) and Silberstein and Grot (1985), as shown inTable J.12, fall within the range observed by Turk et al. (1987). The studies by Weschler et al.(1994), Dietz and Goodrich (1995), and Fisk et al. (2000) also fall within the same range. Thestudy of a laboratory/office complex by Weschler et al. (1989) has two values outside this range,4.0 and 8.2 h-1. However, maximum values of 11.77 and 45.6 h-1 were used by Murray andBurmaster (1995) and Pandian et al. (1993), respectively.

While the data on commercial building air exchange rates are limited, the distribution ofrates is expected, in part because of human comfort considerations, to be similar to residentialstructures when averaged over the United States for all four seasons of the year. Thus, a genericlognormal distribution has been assigned to the building exchange rate to represent average overall conditions. The mean and standard deviation of the distribution are those obtained by Turk etal. (1987), 1.52 h-1 and 0.88, respectively. As discussed above, the mean falls within the averagemean found by different residential studies and is consistent with other commercial buildingstudies. The standard deviation is the same as observed by Murray and Burmaster (1995).Because of the limited data set and variations across different industries, climates, and seasons,this distribution is only an approximation to potential building air exchange rates for lightindustry. Figure J.9 displays the probability density function for the building air exchange rate.The same lognormal distribution is assigned to room exchange rates because the building airexchange rate is an average of the rooms within.

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TABLE J.11 Residential Air Exchange Rate (h-1) Distribution Characteristics

DistributionType Min. Max. Mean SD Comments References

Lognormal 0.30.20.30.70.2

2.22.32.21.42.3

0.90.60.51.00.8

1.81.82.11.31.8

Charleston, S.C. (n = 20 houses)Colorado Springs, Colo. (n = 16 houses)Fargo, N.D. (n = 11 houses)Portland, Maine (n = 11 houses)All cities (n = 58 houses)Calculated infiltration rates based on post-weatherizationmeasurements of “effective leakage area.”

Doyle et al. 1984

Normal0.360.18

0.220.10

0.710.56

0.690.33

0.620.33

0.490.20

0.250.14

0.110.08

Pre-retrofit in one house:n = 17 measurements with fan onn = 11 measurements with fan offPost-retrofit in one house:n = 16 measurements with fan onn = 11 measurements with fan off

Berk et al. 1981

Normal 0.08 0.27 0.17 0.06 n = 12 energy-efficient houses Lipschutz et al. 1981

Lognormal 0.10.1

3.13.6

0.5 median0.9 median

n = 312 houses in North AmericaSubsample of low-income housing

Grimsrud et al. 1983, ascited in Godish 1989

Lognormal 0.170.18

1.331.45

0.33 median0.36 median

n = 8 mobile home measurementsn = 10 UFF-insulated home measurements

Godish and Rouch 1988

Normal0.220.47

0.500.78

0.350.63

0.080.10

n = 9 houses in upstate New YorkWith mechanical ventilation offWith mechanical ventilation on

Offermann et al. 1985

Normal0.400.23

0.981.00

0.270.30

n = 10 houses in Washington statePre-weatherization retrofitPost-weatherization retrofit

Lamb et al. 1985

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TABLE J.11 (Cont.)

DistributionType Min Max Mean SD Comments References

Lognormal0.89 3.44 All regions (n = 1,836) geometric mean, SD Pandian et al. 19930.34 1.88 Northwest (n = 423)0.40 2.07 Northeast (n = 423)1.86 3.02 Southwest (n = 990)1.99 3.28 All regions (n = 1,836) arithmetic mean, SD0.42 0.33 Northwest (n = 423)0.60 2.23 Northeast (n = 423)3.25 3.79 Southwest (n = 990)

0.76 0.88 All regions All seasons (n = 2844)0.55 0.47 All regions Season 1 (n = 1139)0.65 0.57 All regions Season 2 (n = 1051) arithmetic mean, SD

Murray and Burmaster1995

1.50 1.53 All regions Season 3 (n = 529)0.41 0.58 All regions Season 4 (n = 125)0.40 0.30 Region 1 All seasons (n = 467)0.55 0.48 Region 2 All seasons (n = 496)0.55 0.42 Region 3 All seasons (n = 332)0.98 1.09 Region 4 All seasons (n = 1,549)

0.66 0.87 West Region (arithmetic mean and SD) Koontz and Rector 19950.57 0.63 North Central Region0.71 0.60 Northeast Region0.61 0.51 South Region0.63 0.65 All

0.47 2.11 West Region (geometric mean and SD)0.39 2.36 North Central Region0.54 2.14 Northeast Region0.46 2.28 South Region0.46 2.25 All

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0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Air Exchange Rate (h-1)

f(x)

Lognormal DistributionUnderlying � = 0.4187Underlying � = 0.88

TABLE J.12 Outside Air Exchange Rates for Commercial Buildings

Building Air ExchangeRate (h-1) Building Description Reference

0.33 � 1.04 Large office buildings Persily and Grot (1985)

0.9 The National Archive Building Silberstein and Grot (1985)

0.0 � 0.5 0.5 � 1.0 1.0 � 1.5 1.5 � 2.0 2.0 � 2.5 2.5 � 3.0 3.0 � 3.5 3.5 � 4.0 4.0 � 4.5

38 commercial buildings studied in the PacificNorthwest during all seasons of the year. Twobuildings were sampled twice at different times ofthe year.

Number of buildings: 3 10 9 8 6 2 0 1 1

Turk et al. (1987)

0.6, 4.0, and 8.2 Three buildings in an office/laboratory complex Weschler et al. (1989)

0.3 � 1.9 1st floor of Burbank, California, office buildingover a 14-month period

Weschler et al. (1994)

2.5 Classroom building on a college campus Dietz and Goodrich (1995)

0.45 � 0.53 and 0.68 � 0.74

Two different floors, each with its own airhandling unit, in the same office building. Rangeof air exchanges observed over a 7-week period.

Fisk et al. (2000)

FIGURE J.9 Building Air Exchange Rate ProbabilityDensity Function

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J.2.7 Flow Rate between Rooms

Definition: These are the rates at which air flows in each direction between adjacent rooms.Different rates may be specified for the flows in the opposite directions. This parameter does notapply to the one-room model.

Parameter Name: Q12 and Q21 (two-room and three-room model); Q23 and Q32 (three-roommodel only)

Units: m3/h Range: Unlimited

Default Value: Not applicable (default one-room model); Q12 and Q21 = 30 m3/h (two-roommodel); Q12 = 0, Q21 = 0, Q23 = 30, and Q32 = 30 m3/h (three-room model)


Discussion: This parameter is not eligible for probabilistic input. The flow rate between roomsdepends strongly on other air quality model parameters, such as the number of rooms and the airexchange rate. For the one-room model, this parameter is not required. In the code, no airexchange is assumed between rooms 1 and 3; therefore, there is no airflow from room 1 toroom 3. For the two-room model, two flow rate parameters (in cubic meters per hour, or m3/h)are required; for the three-room model, four flow rate parameters are required. The net flowcorresponds to the net volume of air exchanged between the two rooms per unit of time.

The net flow rate between two rooms may be positive, zero, or negative. The net inflowrate from room 1 to room 2 can be negative, which means that the net airflow is from room 2 toroom 1. In the two-room model, the net flow between the two rooms must be balanced with theoutside airflow into or out of each room. In the three-room model, the net flow between the firstand second rooms must equal the sum of the net flow between the second and third rooms plusthe outside airflow into or out of each room. The same logic is true when the net flow betweenthe second and third room is being calculated. The measurement of the net flow between tworooms may be estimated from building specifications for the ventilation system.

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J.2.8 Outdoor Inflow and Outflow

Definition: These are the rates at which air flows between the room and the exterior of thebuilding. In a one-room building, the rate at which the outdoor air flows into the room will beequal to the rate at which the air flows from the room to the exterior. These rates are notnecessarily equal in multiroom buildings; they will only be equal if there is no net air flowbetween the adjoining rooms.

Parameter Name: Q10 and Q01 (one-, two-, and three-room model); Q20 and Q02 (two-roomand three-room model); Q30 and Q03 (three-room model only)

Units: m3/h Range: unlimited

Default Value: (default one-room model); Q10 = Q01 = 72 m3/h (one-room model);Q10 = Q01 = 84 m3/h and Q20 = Q02 = 60 m3/h (two-room model); Q10 = Q01 = 96 m3/h andQ20 = Q02 = Q30 = Q03 = 60 m3/h (three-room model)


Discussion: This parameter is not eligible for probabilistic input. The outdoor inflow andoutflow parameters strongly depend on other air quality model parameters, such as the number ofrooms and air exchange rate. For the one-room model, this parameter is not required. For thetwo-room model, four flow parameters (in m3/h) are required; for the three-room model, six flowparameters are required. The net outdoor flow rate (inflow-outflow) like the net flow ratebetween rooms may be positive, zero, or negative. Increasing or decreasing this parameter willaffect other dependent airflow parameter values. The measurement of net flow between tworooms may be estimated from building specifications for the ventilation system.

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J.2.9 References

Abt, E., et al., 2000, “Relative Contribution of Outdoor and Indoor Particle Sources to IndoorConcentrations,” Environ. Sci. Technol. 34:3579–3587.

American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc., 1997, 1997ASHRAE Handbook, Fundamentals, SI Ed., Atlanta, Ga.

ASHRAE � See American Society of Heating, Refrigerating and Air-Conditioning Engineers,Inc.

Bailey, J.C., and R.C. Rohr, 1953, “Air-Borne Contamination Resulting from TransferableContamination on Surfaces,” K-1088, U.S. Atomic Energy Commission, Washington, D.C.

Barnes, D.E., 1959, “Basic Criteria in the Control of Air and Surface Contamination,” inSymposium on Health Physics in Nuclear Installations, Risø, Denmark, May.

Becher, A.F., 1959, pp. 151–156 in Proceedings of the Symposium on Occupational HealthExperience and Practices in the Uranium Industry, HASL-58, U.S. Atomic Energy Commission,Washington, D.C.

Berk, J.V., et al., 1981, Impact of Energy-Conserving Retrofits on Indoor Air Quality inResidential Housing, LBL-12189, Lawrence Berkeley Laboratory, Berkeley, Calif.

Beyeler, W.E., et al., 1999, Residual Radioactive Contamination from Decommissioning:Parameter Analysis, NUREG/CR-5512, Vol. 3 Draft, U.S. Nuclear Regulatory Commission,Office of Nuclear Regulatory Research, Washington, D.C.

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Carter, R.F., 1970, The Measurement of Asbestos Dust Levels in a Workshop Environment,A.W.R.E. Report No. 028/70, United Kingdom Atomic Energy Authority, Aldermaston, UnitedKingdom.

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Cortissone, C., et al., 1968, “La Contaminazione dell’aria Risultante da Risospensione diContaminazione di Superficie [Atmospheric Contamination from Resuspension of SurfaceContamination],” Minerva Fisiconucleare, Giornal di Fisica Sanitaria Protezione Radiazione,12:63–79.

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Nazaroff, W.W., et al., 1993, “Critique of the Use of Deposition Velocity in Modeling Indoor AirQuality,” pp. 148–165 in N.L. Nagda (editor), Modeling of Indoor Quality and Exposure, ASTMSTP 1205, American Society for Testing and Materials, Philadelphia, Penn.

Nero, A.V., 1988, “Radon and Its Decay Products in Indoor Air: An Overview,” inW.W. Nazaroff and A.V. Nero (editors), Radon and Its Decay Products in Indoor Air, JohnWiley & Sons, New York, N.Y.

Offermann, F.J., et al., 1985, “Low Infiltration Housing in Rochester, New York: A Study of Air-Exchange Rates and Indoor Air Quality,” Environment International 8:435–445.

Pandian, M.D., et al., 1993, “Residential Air Exchange Rates for Use in Indoor Air and ExposureModeling Studies,” Journal of Exposure Analysis and Environmental Epidemiology3(4):407-416.

Persily, A.K., and R.A. Grot, 1985, “Ventilation Measurements in Large Office Buildings,”ASHRAE Trans. 91(2A):488–502.

Roed, J., and R.J. Cannell, 1987, “Relationship between Indoor and Outdoor AerosolConcentration following the Chernobyl Accident,” Radiat. Prot. Dosim. 21:107–110.

Ruhter, P.E., and W.G. Zurliene, 1988, “Radiological Conditions and Experiences in theTMI-Auxiliary Building,” CONF-881-24-9.

Sansone, E.B., 1987, “Redispersion of Indoor Surface Contamination,” in Vol. 1 of K.L. Mittal(editor), Treatise on Clean Surface Technology, Plenum Press, New York, N.Y.

Schultz, N.B., and A.G. Becher, 1963, “Correlation of Uranium Alpha Surface Contamination,Airborne Concentrations, and Urinary Excretion Rates,” Health Phys. 9:901-909.

Sehmel, G.A., 1980, “Particle and Gas Dry Deposition: A Review,” Atmos. Environ. 14:983–1011.

Seinfeld, J.H., and S.N. Pandis, 1998, Atmospheric Chemistry and Physics, John Wiley & Sons,Inc., New York, N.Y.

Shapiro, J., 1970, “Tests for the Evaluation of Airborne Hazards from Radioactive SurfaceContamination,” Health Phys. 19:501–510.

Sherman, M.H. (editor), 1990, Air Change Rate and Air Tightness in Buildings, AmericanSociety for Testing and Materials, Philadelphia, Penn.

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Silberstein, S., and R.A. Grot, 1985, “Air Exchange Rate Measurements in the National ArchiveBuilding,” ASHRAE Trans. 91.

Sinclair, J.D., et al., 1985, “Indoor/Outdoor Concentrations and Indoor Surface Accumulations ofIonic Substances,” Atmos. Environ. 19:315–323 (as cited in Nazaroff and Cass 1989).

Spangler, D.L., 1998, “Re-Suspension Factor Determination and Comparison Using Data froman Operating Licensed Facility” and associated transcript, BWX Technologies, Inc., presented atNRC Decommissioning Workshop, Dec. 1.

Tagg, B., 1966, “Determination of the Resuspension of Plutonium Arising from ContaminatedSurfaces in a Plutonium Operational Area,” in Proceedings of the International Symposium onthe Radiological Protection of the Worker by the Design and Control of His Environment,Society for Radiological Protection, Bournemouth, England, Apr. 18–22.

Thatcher, T.L., and D.W. Layton, 1995, “Deposition, Resuspension, and Penetration of Particleswithin a Residence,” Atmos. Environ. 29(13):1487–1497.

Turk, B.H., et al., 1987, Indoor Air Quality and Ventilation Measurements in 38 PacificNorthwest Commercial Buildings, LBL-22315, Lawrence Berkeley Laboratory, Berkeley, Calif.

U.S. Environmental Protection Agency, 1997, Exposure Factors Handbook, Update to ExposureFactors Handbook, EPA/600/8-89/043 — May 1989, EPA/600/P-95/002Fa,b&c, National Centerfor Environmental Assessment, Office of Research and Development, U.S. EnvironmentalProtection Agency Washington, D.C., Aug.

Utnage, W.L., 1959, “Is There Significant Correlation between Alpha Surface Contamination andAir Concentration of Radioactive Particles in a Uranium Feed Material Plant?” pp. 147–150 inProceedings of the Symposium on Occupational Health Experience and Practices in theUranium Industry, HASL-58, U.S. Atomic Energy Commission, Washington, D.C.

Vette, A.F., et al., 2001, “Characterization of Indoor-Outdoor Aerosol ConcentrationRelationships during the Fresno PM Exposure Studies,” Aerosol Sci. Technol. 34:118–126.

Wallace, L., et al., 1997, “Continuous Measurements of Particles, PAH, and CO in an OccupiedTownhouse in Reston, VA,” in Measurement of Toxic and Related Air Pollutants: Proceedingsof a Specialty Conference, April 29–May 1, 1997, Research Triangle Park, N.C., sponsored byAir & Waste Management Association, Pittsburgh, Penn.

Weschler, C.J., et al., 1989, “Indoor Ozone Exposures,” JAPCA 39:1562–1568.

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Weschler, C.J., et al., 1994, “Indoor Chemistry Involving O3, NO, and NO2 as Evidenced by14 Months of Measurements at a Site in Southern California,” Environ. Sci. Technol. 28:2120–2132.

Whitby, K.T., and G.M. Sverdrup, 1980, “California Aerosols: Their Physical and ChemicalCharacteristics,” p. 495 in G.M. Hidy et al. (editors), The Character and Origins of SmogAerosols, John Wiley & Sons, Inc., New York, N.Y. (as cited in John 1993).

Wrixon, A.D., et al., 1979, “Derived Limits for Surface Contamination,” NRPB-DL2, NationalRadiological Protection Board, Harwell, Didcot, Oxon, United Kingdom.

Yu, C., et al., 2000, Development of Probabilistic RESRAD 6.0 and RESRAD-BUILD 3.0Computer Codes, NUREG/CR-6697, ANL/EAD/TM-98, Argonne National Laboratory,Argonne, Ill., Dec.

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J.3 RECEPTOR PARAMETERS

J.3.1 Number of Receptors

Definition: This parameter represents the number of individuals who are the subjects of the doseassessment.

Parameter Name: ND Units: Unitless Range: Integer values from 1 to 10, inclusive

Default Value: 1

Window: Receptor Parameters

Discussion: This parameter is not eligible for probabilistic input. The number of receptorparameters may or may not represent the actual number of exposed receptors. The number ofreceptors may be used to represent (1) a number of different locations occupied by the sameindividual at different times or (2) a number of different individuals with similar characteristicswho occupy the same location (see Section J.3.4 on the receptor time fraction). Therefore, eachreceptor does not necessarily represent a unique individual; rather, it helps define thecharacteristics of the one or more individuals who are the targets of the dose assessment.

One to 10 receptors may be defined, each with associated parameters such as locationwithin a building or room, time fraction at each location, and inhalation/ingestion rates. Thenumber of receptors may be estimated on the basis of anticipated occupancy patterns or thepurpose of the dose assessment. If a dose assessment is to be performed for a single individualwho will be in only one room at a fixed location during the assessment period, the number ofreceptors is one. This case will also be true if the individual is expected to be at various locationswithin the room, and there are no significant sources of direct gamma radiation. However, ifthere are gamma radiation sources, the dose rate to the individual may depend on the location,and a number of receptors greater than one may be defined to represent various points within theroom with different direct gamma dose rates. The time fraction spent by the individual at eachlocation (see Sections J.3.3 and J.3.4 on receptor location and receptor time fraction,respectively) may then be estimated on the basis of actual experience or anticipated occupancypatterns such as those found in time-motion studies.

If a dose assessment is to involve multiple individuals (collective dose assessment), thenumber of receptors could still be one if all the individuals will be in only one room (possibly atvarious locations), and there are no significant sources of direct gamma radiation. Also, a singlereceptor may be used to represent multiple individuals of whom two or more may be in the samelocation at different times (e.g., shift work). Multiple receptor locations will have to be defined

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when multiple individuals occupy different rooms, or when the direct gamma dose rate is afunction of location and a significant component to the total dose.

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J.3.2 Receptor Room

Definition: This parameter specifies the room in which a receptor is located.

Parameter Name: DLVL Units: Unitless Range: Integer value of 1, 2, or 3

Default Value: 1


Discussion: This parameter is not eligible for probabilistic input. Each receptor must be locatedin one of up to a maximum of three rooms allowed by the code. The identification of the room inwhich a receptor is located affects the air pathways but not the direct gamma radiation pathway.If only one room has been defined, the receptor room will be one. If two rooms have beendefined, a receptor may be placed in room 1 or 2. If three rooms have been defined, a receptormay be placed in room 1, 2, or 3.

Placement of a receptor in one of up to three rooms will depend on site-specific andscenario-specific assumptions. The number of rooms must first be defined (see Section J.2.1 onthe number of rooms) before a receptor may be located in one of them. The code then requiresthat, for each receptor, the receptor room be set at an integer value of 1, 2, or 3. The maximumvalue of the receptor room is determined by the number of rooms.

If a scenario that was originally set up for a two- or three-room model is modified byremoving a room, any receptors previously located in rooms 2 or 3 are automatically relocated toroom 1; however, their spatial coordinates are not changed. The user is advised to reevaluate thenumber of receptors, receptor rooms, and receptor locations before running the modifiedproblem.

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J.3.3 Receptor Location

Definition: This parameter specifies the spatial coordinates of the point (x,y,z Cartesiancoordinate system) occupied by a receptor.

Parameter Name: DX Units: Meters (m) Range: Unlimited

Default Value: 1,1,1


Discussion: This parameter is not eligible for probabilistic input. The receptor location isimportant only to assess direct external gamma exposure from a source; all other pathways makeuse of the room in which the receptor is located (see Section J.3.2 on the receptor room) to assessthe dose. The spatial coordinates (x, y, and z) of the receptor location may be in one of threerooms inside the building. In addition, the spatial coordinates must be within the designatedroom. Typically, a dose assessment is made at 1 meter above the floor over which the receptor islocated. However, different geometrical considerations may reduce or increase this number(e.g., if the receptor is working at heights or sleeping). Also, since a receptor is represented in thecode by using a single point defined by Cartesian coordinates, points that are physicallyinappropriate for human receptors should be avoided (e.g., in contact with or within a source orbuilding structure).

The receptor location is important only for assessing direct external gamma exposurefrom a source. The average location within a room may be used to establish the receptor location.However, if the receptor might be at different points inside a room where the direct gammaradiation contribution might vary significantly, it might be useful to assess more than onereceptor location within the room and adjust the receptor time fraction accordingly. The receptorlocation parameter may also be used to assess the collective dose impact on a number ofreceptors occupying the room at the same time, or it may be used to assess the total dose to asingle receptor that spends time in more than one room.

The code requires that, for each receptor, a location must be entered with spatialcoordinates (in meters) for the receptor midpoint relative to the selected origin. The user mustensure that these coordinates are appropriate for the room’s dimensions. For all source types, asource may not be located at the same coordinates as a receptor. For volume and area sources, thereceptor coordinates may not be located on the same plane as the source surface. For line sources,the receptor coordinates may not be located on the same line as the source.

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J.3.4 Receptor Time Fraction

Definition: This parameter specifies the fraction of time spent by one or more receptors at agiven location while inside the building.

Parameter Name: TWGHT Units: Unitless Range: > 0

Default Value: 1


Distribution: This parameter is not eligible for probabilistic input. If only a single receptor ismodeled, the time fraction spent at any location inside the building may be any number greaterthan zero but less than or equal to 1. If a single receptor spends time at more than one location,the sum of the time fractions at each location should not exceed 1. If multiple receptors aremodeled and more than one receptor is assumed to spend time at the same location, thisparameter may exceed 1 (see Section J.3.3 on the receptor location). The total receptor time spentby one or more receptors inside the building is given by the product of the sum of receptor timefractions at each location, the indoor fraction, and the total time for dose evaluation.

The receptor time fraction may be estimated on the basis of anticipated occupancypatterns. For example, if a single receptor is always inside the same room while inside thebuilding, the receptor time fraction is 1. However, if the room is used by more than one occupant(e.g., shift work), the receptor time fraction may be greater than 1, and the resulting dose at thereceptor location should be interpreted as a collective dose. The user must ensure that the sum ofreceptor time fractions for all receptor locations does not exceed the number of buildingoccupants. The determination of receptor time fractions may be made according to predictedoccupancy patterns for the type of occupancy anticipated inside the building.

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J.3.5 Receptor Breathing/Inhalation Rate

Definition: This parameter reflects the rate at which an individual inhales air at the receptorlocation.

Parameter Name: BRTRATE Units: m3/d Range: ��


Probabilistic Analysis Default Distribution: TriangularDefining Values for Distribution:Minimum: 12 Maximum: 46 Most likely: 33.6


Discussion: If more than one receptor location is chosen, the breathing rate at each location mustbe specified. If inhalation pathways are not analyzed in a scenario, the inhalation rate can be setto zero. The range of estimates of inhalation rate (Table J.13) reflects the differences in patternsof time and activity levels, as well as age, sex, and weight of the individual. Until recently,inhalation rates for the “reference man and woman,” as described by the InternationalCommission on Radiological Protection (ICRP 1975), were often used as default values. TheICRP best estimates, which are based on 16 hours of light activity and 8 hours of rest, are asfollows: 23 m3/d (range of 23–31 m3/d) for adult males; 21 m3/d (range of 18–21 m3/d) for adultfemales; and 15 m3/d for a 10-year-old child. By using different patterns for the time and activitylevels, the EPA has proposed a wider range of adult inhalation rates but recommends essentiallythe same point estimates as the ICRP for “average” adults (EPA 1985, 1989, 1991, 1997).

The distribution varies widely because of differences in time-use activity patterns that aredeveloped for outdoor/indoor and occupational/residential exposures. Because activity levels ofvarious individuals and groups can vary to a significant extent, it is preferable to derive a rangeof inhalation rates by using activity data specific for the population under study. The dailyaverage inhalation rate in RESRAD-BUILD is meant to represent workers in an occupationalsetting. For assessments involving other specific activities, inhalation rates can be selected thatare thought to be representative of these particular activities. Similarly, if receptors of a certainage group are being evaluated, breathing rate values should be selected specifically for that agegroup.

Layton (1993) proposed three alternative approaches for deriving inhalation rates that arebased on oxygen uptake associated with energy expenditures: (1) average daily intakes of foodenergy from dietary surveys, (2) average daily energy expenditure calculated from ratios of totaldaily expenditure to basal metabolism, and (3) daily energy expenditures determined from atime-activity survey. These approaches consistently yield inhalation rate estimates that are lower

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than the EPA’s best “reasonable worst case” estimates and ICRP (1975) reference values.Layton’s inhalation rate estimates fall in the recommended range and may be more accuratevalues for point estimates. However, the approach needs to be further reviewed and validated inthe open literature before these lower, less conservative inhalation rate estimates are used.

The available studies on inhalation rates have been summarized by the EPA (1997).Inhalation rates are reported for adults and children (including infants) performing variousactivities and for outdoor workers and athletes. The activity levels have been categorized asresting, sedentary, light, moderate, and heavy. Table J.14 summarizes inhalation rate valuesrecommended by the EPA both for long-term and short-term exposure. The daily averageinhalation rates for long-term exposure for adults are 11.3 m3/d for women and 15.2 m3/d formen.

A default triangular distribution is used for input to RESRAD-BUILD for a buildingoccupancy scenario. The most likely inhalation rate value was taken to be 33.6 m3/d (1.4 m3/h),as recommended in Beyeler et al. (1998). The minimum value of 12 m3/d (0.5 m3/h) was selectedon the basis of recommendations for sedentary adult activities, and a maximum value of 46 m3/d(1.9 m3/h) was selected because it represented the highest average value reported in Beyeler et al.(1998) for workers in light industry and falls within the range of moderate to heavy activities forboth adults and outdoor workers (Table J.14). Figure J.10 presents the probability densityfunction for the default inhalation rate distribution.

As discussed above, the breathing rates of individuals are a well-measured parameter thatrequire no additional site-specific measurements unless the receptors involved are significantlydifferent from the average individual. On the basis of the assumed exposure scenario andanticipated activity profile, the average breathing rate for a receptor location may be estimated byusing time-weighted inhalation rates for the different receptor types and activity levels presentedin Table J.14. The code requires that the average breathing rate (in m3/d) be defined for eachreceptor location. The default deterministic value is 18 m3/d. Setting this parameter to zeroeffectively suppresses the dust inhalation pathway.

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TABLE J.13 Inhalation Rate Distributions

Inhalation Rate (m3/d)

BasisDistribution

Type Min. Max. MeanMost

Likely References

Based on time-weighted average food-energy intakes adjusted for reporting bias

Triangular Layton 1993

Males (lifetime average) Females (lifetime average)

139.6

1713

14 10

Based on average age-adjusted dailyenergy expenditure rates


Males (18–60+ yr) Females (18–60+ yr)

139.9

1711

15 11

Based on age-adjusted activity patternsand metabolic rates for an “average day”


Males (20–74 yr) Females (20–74 yr)

1311

1715

16 13

“Reference man” - Based on light activity(16 hours) and resting (8 hours)

Triangular ICRP 1975

Adult male Adult female Child

2318

-

3121 -

23 21 15

Based on “typical” outdoor activity levelsa Triangular EPA 1985, 1989, 1991 Adult female Adult male Average adult

1713

-

7079 -

254034

20 20 20

Based on “typical” indoor activity levelsb Triangular EPA 1985, 1989, 1991 Adult female Adult male Average adult

74-

3438

-

112115

15 15 15

Study of age-dependent breathing rates atrealistic activity levels

- Roy and Courtay 1991

0–0.5 yr 1.62 0.5–2 yr 5.14 2–7 yr 8.71 7–12 yr 15.3 12–17 yr 17.7

a Resting: 28%, light activity: 28%, moderate activity: 37%, heavy activity: 7%.

b Resting: 48%, light activity: 48%, moderate activity: 3%, heavy activity: 1%.

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TABLE J.14 Summary of EPA’s RecommendedValues for Inhalation

PopulationMean(m3/d) Population

Mean(m3/h)

Long-Term Exposures Short-Term Exposures Infants (<1 year) 4.5 Adults

Rest 0.4 Children Sedentary activities 0.5 1–2 years 6.8 Light activities 1.0 3–5 years 8.3 Moderate activities 1.6 6–8 years 10 Heavy activities 3.2 9–11 years Males 14 Children Females 13 Rest 0.3 12–14 years Sedentary activities 0.4 Males 15 Light activities 1.0 Females 12 Moderate activities 1.2 15–18 years Heavy activities 1.9 Males 17 Females 12 Outdoor Workers

Hourly averagea 1.3 Adults (19–65+yrs) Slow activities 1.1 Females 11.3 Moderate activities 1.5 Males 15.2 Heavy activities 2.5

a Upper percentile = 3.3 m3/h.

Source: EPA (1997).

J-65

FIGURE J.10 Inhalation Rate Probability Density Function

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0 10 20 30 40 50

Inhalation Rate (m3/d)

f(x)


Minimum = 12 m3/d

Maximum = 46 m3/d

Most Likely = 33.6 m3/d

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J.3.6 Indirect Ingestion Rate

Parameter Name: INGE2

Definition: This parameter represents the ingestion rate of deposited material for a receptor at aspecified location inside the building. This rate represents the transfer of deposited contaminationfrom building surfaces to the mouth via contact with hands, food, or other objects. The indirectingestion rate is expressed as the surface area contacted per unit time. This rate is different fromthe direct ingestion rate, since an individual does not need to be in the same room as the source tobe exposed by this pathway.

Parameter Name: INGE2 Units: m2/h Range: ��


Probabilistic Analysis Default Distribution: loguniformDefining Values for Distribution:Minimum: 2.8 × 10-5 Maximum: 2.9 × 10-4


Discussion: Only limited information is available on the values for this parameter. As reported inBeyeler et al. (1998), only eight data references are available (Dunster 1962; Gibson and Wrixon1979; Healy 1971; Kennedy et al. 1981; Sayre et al. 1974; Lepow et al. 1975; Walter et al. 1980;Gallacher et al. 1984). However, half of these studies concerned intake by children, not adults inan occupational setting. A larger, secondary set of data from soil ingestion studies is available(see Section J.4.8). Again, however, the primary emphasis has been soil ingestion rates ofchildren because of concern over elevated exposures from intensive mouthing behavior in thisage group. Only two studies (Calabrese et al. 1990; Stanek et al. 1997) have provided empiricaldata for soil ingestion by adults. Comprehensive reviews of soil ingestion by humans can befound in EPA (1997) and Simon (1998).

Because the indirect ingestion rate is specified as the surface area contacted per unit time,estimates of the daily ingested amount were converted to the proper units by using estimates fordeposited contamination (soil) concentrations on surfaces and soil loadings on the hand (Beyeleret al. 1998). Thus, a large uncertainty for the indirect ingestion rate is expected; in fact, theuncertainty is larger than the anticipated variability across sites (Beyeler et al. 1998). For thisreason, Beyeler et al. (1998) have proposed two alternative distributions. However, Beyeler’ssuggested procedure produces an effective ingestion rate. It incorporates the number of hand-to-mouth events per day and transfer efficiencies between surface-to-hand and hand-to-mouth,because these factors were not explicitly accounted for in the calculation.

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The two alternative distributions were proposed on the basis of mean ingestion rates of0.5 and 50 mg/d. These rates fall within the 0 to 70 mg/d range for mean ingestion rates thoughtto be consistent with the empirical data (Calabrese et al. 1990; Calabrese and Stanek 1995;Stanek et al. 1997). The minimum and maximum ingestion rates were taken to be 0 and200 mg/d, respectively. In the most comprehensive study, 10 subjects were followed for 28 days,yielding an average ingestion rate of 10 mg soil/d, with an upper 95% value of 331 mg soil/d(Stanek et al. 1997). Dust loadings were assumed to range from 10 mg/m2, taken to be the lowerlimit in a residential setting, to 5,000 mg/m2, taken to correspond to heavily soiled hands.

The resulting loguniform distributions (Table J.15) for the indirect ingestion rateparameter ranged from 4.4 × 10-4 to 4.6 × 10-3 m2/d, with a mean of 1.8 × 10-3 m2/d; and from5.1 × 10-2 to 4.3 × 10-1 m2/d, with a mean of 1.8 × 10-1 m2/d. For use in RESRAD-BUILD, a16-hour day was assumed, resulting in distributions with means of 1.1 × 10-4 and 1.1 × 10-2 m2/hfor the low and high average ingestion rate distributions presented in Table J.15. As discussed inBeyeler et al. (1998), an ingestion rate corresponding to 1 × 10-2 m2/h implies mouthing an areaequivalent to the inner surface of the hand once each hour. Such an ingestion rate appears to bean upper bound for a commercial environment. Because adult ingestion rates can often approachzero (the lower bound), the lower ingestion rate distribution has been selected as a default for usein RESRAD-BUILD. Figure J.11 presents the probability density function.

The code requires that the average indirect ingestion rate in m2/h be defined for eachreceptor location. The default deterministic value of 0.0001 m2/h is consistent with the meanvalue of the default probabilistic input distribution. Setting this parameter to zero effectivelysuppresses the indirect ingestion pathway.

TABLE J.15 Indirect Ingestion Rates

Parameter Mean Lower Limit Upper Limit

From Beyeler et al. 1998 Dust loading (mg/m2) 320 10 5,000 Low ingestion rate input (mg/d) 0.50 0 200 High ingestion rate input (mg/d) 50 0 200 Low ingestion rate estimate (m2/d) 1.8 � 10-3 4.4 � 10-4 4.6 � 10-3

High ingestion rate estimate (m2/d)1.8 � 10-1 5.1 � 10-2 4.3 � 10-1

RESRAD-BUILD Inputa

Low ingestion rate estimate (m2/h) 1.1 � 10-4 2.8 � 10-5 2.9 � 10-4

High ingestion rate estimate (m2/h) 1.1 � 10-2 3.2 � 10-3 2.7 � 10-2

a Assumes a 16-hour day using the results from Beyeler et al. (1998).

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FIGURE J.11 Indirect Ingestion Rate Probability Density Function

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

18,000

0.00001 0.0001 0.001

Indirect Ingestion Rate (m2/h)

f(x)


Minimum = 2.8 � 10-5 m2/d

Maximum = 2.9 � 10-4 m2/d

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J.3.7 References

Beyeler, W.E., et al., 1998, “Review of Parameter Data for the NUREG/CR-5512 BuildingOccupancy Scenario and Probability Distributions for the DandD Parameter Analysis,” letterreport prepared by Sandia National Laboratories, Albuquerque, N.M., for U.S. NuclearRegulatory Commission, Wash., Jan.

Calabrese, E.J., and E.J. Stanek, 1995, “Resolving Intertracer Inconsistencies in Soil IngestionEstimation,” Environmental Health Perspectives 103(5):454–57.

Calabrese, E.J., et al., 1990, “Preliminary Adult Soil Ingestion Estimates: Results of a Pilot-Study,” Regulatory Toxicology and Pharmacology 12(1):88–95.

Dunster, H.J., 1962, Maximum Permissible Levels of Skin Contamination, AHSB(RP)R28,United Kingdom Atomic Energy Authority, London, England.


Gallacher, J.E.J., et al., 1984, “Relation between Pica and Blood Lead in Areas of Differing LeadExposure,” Archives of Disease in Childhood 59:40–44.

Gibson, J.A.B., and A.D. Wrixon, 1979, “Methods for the Calculation of Derived WorkingLimits for Surface Contamination by Low-Toxicity Radionuclides,” Health Physics (36)3:311–321.

Healy, J.W., 1971, Surface Contamination: Decision Levels, LA-4558-MS, Los Alamos NationalLaboratory, Los Alamos, N.M.

ICRP: See International Commission on Radiological Protection.

International Commission on Radiological Protection, 1975, Report of the Task Group onReference Man, ICRP Publication 23, prepared by a Task Group of Committee 2, adopted by theCommission in Oct. 1974, Pergamon Press, New York, N.Y.

Kennedy, W.E., Jr., et al., 1981, A Review of Removable Surface Contamination on RadioactiveMaterials Transportation Containers, NUREG/CR-1859, PNL-3666, U.S. Nuclear RegulatoryCommission, Washington, D.C.

Layton, D.W., 1993, “Metabolically Consistent Breathing Rates for Use in Dose Assessments,”Health Physics 64(1):23–36.

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Lepow, M.L., et al., 1975, “Investigations into Sources of Lead in the Environment of UrbanChildren,” Environ. Res. 10:414–426.

Roy, M., and C. Courtay, 1991, “Daily Activities and Breathing Parameters for Use inRespiratory Tract Dosimetry,” Radiation Protection Dosimetry 35(3):179–186.

Sayre, J., et al., 1974, “House and Hand Dust as a Potential Source of Childhood LeadExposure,” Am. J. of Dis. Chil. 127:167–170.

Simon, S.L., 1998, “Soil Ingestion by Humans: A Review of History, Data, and Etiology withApplication to Risk Assessment of Radioactively Contaminated Soil,” Health Physics74(6):647–672.

Stanek, E.J., et al., 1997, “Soil Ingestion in Adults — Results of a Second Pilot-Study,”Ecotoxicology and Environmental Safety 36:249–257.

U.S. Environmental Protection Agency, 1985, Development of Statistical Distributions orRanges of Standard Factors Used in Exposure Assessments, EPA/600/8-85/010, Office of Healthand Environmental Assessment, Washington, D.C.

U.S. Environmental Protection Agency, 1989, Exposure Factors Handbook, EPA/600/8-89/043,Office of Health and Environmental Assessment, Washington, D.C.

U.S. Environmental Protection Agency, 1991, Risk Assessment Guidance for Superfund,Volume I, Human Health Evaluation Manual, Supplemental Guidance, Standard DefaultExposure Factors, Interim Final, OSWER Directive 9285.6-03, Office of Emergency andRemedial Response, Washington, D.C.

U.S. Environmental Protection Agency, 1997, Exposure Factors Handbook, Update to ExposureFactors Handbook, EPA/600/8-89/043 — May 1989, EPA/600/P-95/002Fa,b&c, National Centerfor Environmental Assessment, Office of Research and Development, Washington, D.C., Aug.

Walter, S.D., et al., 1980, “Age-Specific Risk Factors for Lead Absorption in Children,” Archivesof Environ. Health 53(1):53–58.

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J.4 SOURCE PARAMETERS

J.4.1 Number of Sources

Definition: The number of sources specifies the number of radioactive source locations to beconsidered in the dose assessment.

Parameter Name: NS Units: Unitless Range: Integer between 1 to 10, inclusive

Default Value: 1

Window: Source Parameters

Discussion: This parameter is not eligible for probabilistic input. One to 10 sources may bedefined, each with associated parameters, such as location within a building or room, source typeand direction, and source details.

The number of sources may be estimated on the basis of the actual number ofindependent radioactive sources present in the building. Single sources may also be broken downinto two or more components on the basis of geometric considerations. For example, a singlecontaminated pipe that makes a 90-degree bend may be modeled as two line sources. An area orvolume source whose length is twice as large as its width may be modeled as two sources ofequal lateral dimensions, since the code models such sources as disks or cylinders, respectively.Another reason to divide a source into two or more components is if it is a heterogeneousdistribution of radionuclides. For example, a source may be volumetrically contaminated withcertain radionuclides but may also have a surface contaminated with different or higherconcentrations of the same radionuclides. The code requires at least one source (and itsassociated geometrical, physical, and radiological characteristics).

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J.4.2 Source Room (also Primary Room)

Definition: The source room or primary room is the room number containing a particular source.

Parameter Name: SLVL Units: Unitless Range: Integer value of 1, 2, or 3

Default Value: 1


Discussion: This parameter is not eligible for probabilistic input. If only one room has beendefined, the source room will be room 1. If two rooms have been defined, a source may be placedin room 1 or 2. If three rooms have been defined, a source may be placed in room 1, 2, or 3. Theidentification of the room in which a source is located affects the air pathways and the directingestion pathway but not the direct gamma radiation pathway.

Placement of a source in one of up to three rooms will depend on site-specific andscenario-specific assumptions. A source may form part of the boundary between two rooms, suchas a wall, floor, or ceiling. In such cases, the user must select a primary room into which anysource material may be initially released. For example, a wall between two rooms may bevolumetrically contaminated, but most of the source is located on one side of the wall. Thesource room would be the one into which most of the contaminants would be released. Foruniform contamination, the user may divide the source into two (see “Number of Sources”)volume sources, both equal in thickness to the original source. Each volume source would becomposed of two layers, one contaminated and one uncontaminated, and each source would beassigned to a separate room. Care must be taken to define each layer of the volume sourcecorrectly (see Sections J.4.13 and J.4.14 on number of regions in volume source andcontaminated region, respectively).

The number of rooms must first be defined (see Section J.2.1 on the number of rooms)before a source may be located in one of them. The code then requires that, for each source, thesource room be set at an integer value of 1, 2, or 3. The maximum value of the source room isdetermined by the number of rooms. If a scenario originally set up for a two- or three-roommodel is modified by removing a room, any sources previously located in rooms 2 or 3 areautomatically relocated to room 1; however, their spatial coordinates are not changed. The user isadvised to reevaluate the number of sources, source rooms, and source locations before runningthe modified problem.

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J.4.3 Source Type

Definition: The source type specifies the geometrical representation of the physical distributionof radioactive material within a source. One of four source types — volume, area, line, orpoint — is selected to represent the best approximation for modeling a source that has a uniformdistribution of radionuclides within it.

Parameter Name: STYPE Units: Unitless Range: Volume, area, line, or point

Default Value: Volume


Discussion: This parameter is not eligible for probabilistic input. Depending on geometricappearance, a source may be represented by one of four types: volume, area, line, or point.

• Volume source: This source has a circular exposed area with some finite depthperpendicular to this area. This means that many details of the buildingcomponent and contamination must be specified. The user may specify up tofive different regions along the thickness of the source.

• Area source: This source has a circular exposed area with no thickness.

• Line source: This source has no thickness or depth.

• Point source: This source has no dimensional or directional characteristics.

The external dose from a source of equal strength could depend strongly on the sourcegeometry. The volume type and other types also are distinguished in the air quality model. Theinjection and radon release models are different.

The source type is not a measurable quantity. However, the source type will determine themeasurement methodology for the source activity or concentration. It may be possible to model asource in more than one way. The determination of which source type to use depends, in part, onengineering judgment. For example, a small area of surface or volume contamination may berepresented as a point source if the largest dimension of the source is at least three times smallerthan the distance between the source and receptor. Similarly, a volumetrically contaminatedsurface may be treated as an area source if the thickness of the contamination is small relative tothe attenuation properties of the source material. A source whose length is at least three timeslarger than width or depth may be treated as a line source.

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The code requires the designation of a source type (volume, area, line, or point) for eachsource represented. At least one source with an assigned type must be represented, and up to atotal of 10 sources, each with an assigned type, may be represented. The source type selected willautomatically adjust the proper input units for source activity or concentration. The selectedsource type will also determine if additional descriptive parameters will be required. At aminimum, the source location will be required (all source types). Other required parameters mayinclude source length (line source), source area (volume and area sources), source direction(volume, area, and line sources), and source thickness (volume source). The code models areasources as disks and volume sources as cylinders.

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J.4.4 Source Direction

Definition: The source direction indicates the direction of a source relative to the three Cartesiancoordinate axes. It applies to line, area, and volume source types. For a line source, the sourcedirection is defined as the axis parallel to the line. For area and volume sources, the sourcedirection is defined as the axis normal to the surface of the source.

Parameter Name: SDIR Units: Unitless Range: x, y, or z axis

Default Value: x axis


Discussion: This parameter is not eligible for probabilistic input. A source must have a directionthat is parallel to one of three main coordinate axes: x, y, or z. In most cases (e.g., buildings withrooms that can be modeled as boxes), a coordinate system can be defined so that line sourceswithin these rooms will run parallel to the major axes, and area and volume sources will havesurfaces that lie on orthogonal planes. If the source is curved or at an angle relative to the majorcoordinate axes, the user must judge whether to model it as an equivalent orthogonal source orrotate the axes to match the direction of the source.

A line source requires a source direction closest to the axis parallel to the line. Area andvolume sources require source directions representing a line drawn normal to the surface of thesource and parallel to the x, y, or z axis. Figure J.12 provides examples of source direction forline and area sources.

FIGURE J.12 Source Direction for Line, Area, andVolume Sources

Z

X

Y

yx

Volumeor Area

Line

Z

X

Y

yx

Volumeor Area

Line

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J.4.5 Source Location

Definition: The source location specifies the spatial position of the source center point in three-dimensional space relative to the origin. Depending on the source type, additional parametersmay be required to define the extent and direction of the source.

Parameter Name: SX Units: Meters (m) Range: Unlimited

Default Value: 0,0,0


Discussion: This parameter is not eligible for probabilistic input. The spatial coordinates (x, y,and z) of the source location may be anywhere inside or outside the building. The user mustensure that the source location is consistent with additional geometrical parameters that may berequired to define the source. The coordinates of the source location are used only to calculatedirect external exposure.

The source location is determined by the number of rooms modeled. For volume sources,radon may diffuse into two rooms through a common wall, but the user must determine theprimary room into which particulates are released. In addition, the location of the source centerpoint must be provided relative to the coordinate system’s origin. For point sources, thecoordinates of the source are all that is required. The measurements for additional parameters areneeded to define the extent of other source types (see Sections J.4.6 and J.4.15 on sourcelength/area and source thickness, respectively). The user is free to place the origin anywhere inthe building; however, the same origin must be used when specifying the locations of thereceptor(s) and source(s). If volume sources are present, the origin must be placed so that thesurface of the source from which the particulate and tritium releases occur is closer to the originthan the other surfaces of the source.

Although the source may be located at any physically allowable point in space, users mustensure that the placement of the source matches the scenario desired. The geometric coordinatesused to define the center point of the source must be entered in meters. At least one pointrepresenting the center of each source must be defined by x, y, and z coordinates measured withrespect to an absolute reference point. For all source types, a source may not be located at thesame coordinates as those occupied by a receptor. For volume and area sources, the receptorcoordinates may not be located on the same plane as the source surface. For line sources, thereceptor coordinates may not be located on the same line as is the source.

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J.4.6 Source Length/Area

Definition: This parameter specifies the extent of the contamination. It is the exposed area for anarea or volume source, or it is the length for a line source. It is not applicable to point sources.

Parameter Name: SAREA Units: m2 (volume or area source), m (line source) Range: > 0

Deterministic Analysis Default Value: 36 (line, area, and volume sources)


Window: Source Parameters → Source Details

Discussion: For calculating direct external gamma doses, the source may have a large extent.However, for all other pathways, the source should be limited to the dimensions of the room intowhich radionuclides are being released.

For a line source, the length of the source must be measured. It is assumed that thecontamination is distributed uniformly along the length. For area and volume sources, the area ofcontamination must be determined. For the area and volume sources, it is assumed that thecontamination is distributed uniformly over the area. Sources whose geometries departsignificantly from the idealized geometries used in the code may be broken down into smallersources (see Section J.4.1 on the number of sources). In addition, the depth of contaminationmust be measured for a volume source (see Section J.4.15 on source thickness).

A line source requires the source length (in meters, or m). Area and volume sourcesrequire the surface area (in square meters, or m2). If room dimensions are changed, the user mustensure that the source dimensions remain consistent with the new room dimensions. The codemodels area sources as disks and volume sources as cylinders.

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J.4.7 Air Release Fraction

Definition: The air release fraction is the amount of the contaminated material removed from thesource that is released into the air in the respirable particulate range.

Parameter Name: AIRFR Units: Unitless Range: 0 to 1


Probabilistic Analysis Default Distribution: TriangularDefining Values for Distribution:Minimum: 1 × 10-6 Maximum: 1 Most likely: 0.07


Discussion: The fraction released to the air is the amount of the contaminated material removedfrom the source that is suspended in air; the balance of the material (1 − AIRFR) is assumed to beinstantaneously removed from the room. The value of this parameter can range from 0 (all erodedmaterial is removed instantaneously from the room) to 1 (all eroded material is suspendedinstantaneously in the respirable room air). This parameter depends strongly on the erosionprocess. Mechanical disturbances, such as sanding, scraping, or chipping, result in a highcontaminant removal rate but usually generate a relatively small fraction of particulates releasedto air. Most of the eroded material tends to fall to the floor and is removed from the room byhousekeeping activities. Dusting results in low erosion rates, but a relatively high fraction ofremoved material may become suspended in air. Vacuuming, on the other hand, may result inhigher erosion rates than would dusting, but a smaller fraction would become airborne; asignificant fraction would be trapped in the vacuum.

The RESRAD-BUILD code requires an air release fraction input for each source.Entering 0 means that none of the removable material will be released to the air that is respirable.The dose contributions from deposition, immersion, dust inhalation, and indirect ingestion areeffectively suppressed. Entering 1 is very conservative because it will maximize the dosecontributions from these pathways. If either the removable fraction (Section J.4.9) or erosion rate(Section J.4.17) are 0, the contributions from these pathways will be suppressed no matter whatvalue is given to the air release fraction.

The DOE handbook on airborne release fractions (ARFs) and respirable fractions (RFs)1

(DOE 1994a) provides a compendium and analysis of experimental data from which ARFs and 1 The airborne release fraction is the amount of radioactive material that can be suspended in air and made available

for airborne transport. The respirable fraction is the fraction of airborne radionuclides as particulates that can betransported through air and inhaled into the human respiratory system. This fraction is commonly assumed to��

J-79

RFs may be derived. The data are given by the physical form of the material affected (e.g., gas,liquid, solid, surface contamination) and different suspension stresses (e.g., spill, thermal stress,shock wave, blast stress). The American Nuclear Society (ANS) has published an Americannational standard for airborne release fractions at nonreactor nuclear facilities (ANS 1998).

For materials in gaseous form, such as H-3, the recommended ARF is 1.0. All materialsin the gaseous state can be transported and inhaled; therefore, the RF is also 1.0 (DOE 1994a).

The DOE handbook provides release fractions for three categories of solid materials:metals, nonmetallic or composite solids, and powders. The bounding ARF for plutonium metalformed by oxidation at elevated temperatures was found to be 3 × 10-5, with an RF value of 0.04.ARF and RF values of 1 × 10-3 and 1.0 were assessed to be bounding during complete oxidationof metal mass (DOE 1994a). The bounding values for contaminated, noncombustible solids werefound to be 0.1 and 0.7 for ARF and RF, respectively (these release values are for loose surfacecontamination on the solid, not the solid as a whole).

Little information is available for building occupancy; therefore, a triangular distributionbased on the above data is used. The maximum value is assumed to be 1 (for gaseous forms), theminimum value chosen is that for plutonium metal (3 × 10-5 × 0.04 = 1.2 × 10-6), and the mode(most likely value) is the bounding value for contaminated noncombustible solids (0.1 × 0.7 =0.07). The probability density function is displayed in Figure J.13.

FIGURE J.13 Air Release Fraction Probability Density Function

0

0.5

1

1.5

2

2.5

0 0.2 0.4 0.6 0.8 1

Air Release Fraction

f(x)


Minimum = 1 × 10-6

Maximum = 1Most Likely = 0.07

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J.4.8 Direct Ingestion Rate

Definition: The direct ingestion rate refers to the incidental ingestion rate of contaminatedmaterial directly from the source.

Parameter Name: INGE1 Units: g/h for volume sources 1/h for point, line, and area sources

Range: ≥ 0




Discussion: This is the direct ingestion rate of the source by any receptor in the room. Eachreceptor will ingest the source at a rate determined by the product of the ingestion rate and theamount of contamination in the source at that time. Direct ingestion is possible only if thereceptor and the source are in the same room. The direct ingestion rate is included in theRESRAD-BUILD code for unlikely events when a receptor could directly ingest source material.Such a receptor could be conducting a maintenance or renovation activity that involved physicalcontact with the source. The direct ingestion rate is normally set to 0 for most calculations.

The magnitude of the direct ingestion rate is highly correlated with other inputparameters. For volume sources, the total amount of material ingested may range from 0 to amaximum specified by the mass of the source (area [Section J.4.6] × thickness [Section J.4.15] ×density [Section J.4.16]). In addition, the direct ingestion rate cannot exceed the amount removedper unit time as determined by the source erosion rate (Section J.4.17). Indirect ingestion(Section J.3.6) must also be taken into account, as must time spent in the room with the source.Also, the direct ingestion rate should not cause the total physical mass of the source to bedepleted over the time of exposure and must take into account the mass balance because oferosion of the source resulting from other mechanisms (Section J.4.17).

For the other source types (point, line, and area), the direct ingestion rate is expressed as afraction of the source ingested per hour. This rate may range from 0 to a value less than or equalto the removal rate that is determined by the removable fraction (Section J.4.9) and the sourcelifetime (Section J.4.10) input parameters. If the direct ingestion rate is large enough to match theremoval rate, then the air release fraction (Section J.4.7) input must be set to 0 to maintain massbalance.

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J.4.9 Removable Fraction

Parameter Name: RMVFR

Definition: The removable fraction is the fraction of a point, line, or area source that can beremoved. The balance of the source is assumed to remain fixed.

Parameter Name: RMVFR Units: Unitless Range: 0 to 1


Probabilistic Analysis Default Distribution: TriangularDefining Values for Distribution:Minimum: 0.0 Maximum: 1.0 Most likely: 0.1


Discussion: The removable fraction can account for various events that reduce the amount ofsource activity over time. In RESRAD-BUILD calculations, this fraction of the source will belinearly removed between time 0 and the source lifetime (Section J.4.10). Source activity may bereduced over a period of time as a result of such events as surface washing (chemical andmechanical action) or foot or equipment traffic if the source is on the floor (mechanical action).Because source activity could remain on a wall indefinitely or be removed entirely because ofheavy traffic across floor contamination, the default distribution for the removable fractionranges from 0 to 1 for use in a triangular distribution. Figure J.14 displays the distribution’sprobability density function.

The DOE Radiological Control Manual (DOE 1994b) allows a maximum removableconcentration that is 20% of the maximum allowable total surface contamination for mostradionuclides except for some transuranics and tritium (Table 2-2 in DOE 1994b). The maximumallowed removable transuranic or tritium contamination is 4% or 100%, respectively, of themaximum allowable surface contamination. However, under these restrictions, conditions mayexist for unrestricted use in cases where the removable surface contamination constitutes 20% ofthe surface contamination for all radionuclides. For the NRC, maximum acceptable removableconcentrations are 10% of the average surface concentrations for all radionuclides (NRC 2000).Like the DOE regulations, however, the removable fraction can be higher than 0.1 if overallsurface concentrations are lower. Thus, a triangular distribution, as shown in Figure J.14, issuggested for the removable fraction, with a most likely value of 0.1 and minimum andmaximum values of 0 and 1, respectively, as discussed above.

For specific situations, a number of factors must be considered, including location of thecontamination (e.g., wall or floor and proximity to human activity), the nature of the

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contaminated surface (e.g., type of material [chemical and physical properties]), the original formof the contaminant (chemical and physical properties [e.g., powder versus liquid and chemicalreactivity]), and the removal mechanism (such as washing or foot traffic).

Smear tests are often used to determine the amount of “fixed” versus “non-fixed” (orremovable) contamination (Frame and Abelquist 1999). Although the definition of removablecontamination varies, it applies to radioactive “contamination which is removable or transferableunder normal working conditions” (International Organization for Standardization [ISO] 1988)or “radioactivity that can be transferred from a surface to a smear test paper by rubbing withmoderate pressure” (NRC 1979a,b) or “radioactive material that can be removed from surfacesby non-destructive means such as casual contact, wiping, brushing, or washing” (DOE 1994b).However, smear tests can vary because of the material of the smear wipes used and the potentialuse of a wetting agent (Frame and Abelquist 1999). Also, smear tests will vary according to thecontaminant, the surface, and the pressure and technique used by each technician performing thetest (Sansone 1987; Jung et al. 2001). Table J.16 lists results from early experiments thatdemonstrate that the nature of the contamination and of the surface can influence how easilyremovable the radioactive contamination can be. Thus, a specific distribution for the removablefraction must be made on a case-by-case basis. Other measurement tests in the past have includedtape and modified air sensor tests. Table J.17 presents some results comparing these methodswith smear tests on different surfaces.

In assigning a removable fraction, a number of factors must be taken into account. In adecommissioned and decontaminated building, any residual contamination might be expected tobe predominantly fixed because decontamination efforts should have used reasonable steps incleaning the building. Weber (1966) demonstrated that up to 99.9% of deposited (dried solution)radioactive surface contamination could be removed in some cases by using the proper cleaningsolution. This removal efficiency is much higher than that shown by smears or other samplingmethods (e.g., see Table J.17). Thus, the removable fraction is highly dependent on thedecommissioning activities used to bring the building surfaces into compliance and future onhousekeeping activities.

No information appears to be available regarding smear tests on freshly cleaned surfaces.Smears may be more indicative of what contamination is available for removal by such processesas resuspension. Multiple smears on the same area may also be used in determining the removalfraction (Frame and Abelquist 1999). Jung et al. (2001) studied the effect of multiple smears onstainless steel (with different surface finishes), aluminum, and titanium metal samples aftersubmersion in a spent fuel storage pool. In each case, the 10th consecutive smear containedapproximately 5 to 10% of the total removed contamination for all 10 smears. Extrapolating theirsmear results for the stainless-steel samples, Jung et al. (2001) estimated the total removablecontamination to be approximately 8 to 11%; the first smear picked up only 2 to 4% of theremovable contamination.

J-83

FIGURE J.14 Removable Fraction Probability Distribution

TABLE J.16 Influence of Surface and Contaminant Types on Smear Tests

Contamination

PercentageContamination

Removed Surface Comments Reference

Low level fromnormal use

1 to 3 Granolithic concrete floor

Brunskill (1967)

50 Water wash of floorPlutoniumnitrate

0.1 to 0.26

PaperWaxed and polished linoleum

Jones and Pond(1967)

20 to 30 Polyvinyl chloride

Plutonium nitrate oroxide in solution wasapplied to the floorand allowed to dryfor 16 hours

PuO2 10 to 20 Polyvinyl chloride20 to 30 Unwaxed linoleum50 to 60 Waxed and polished

linoleum

0

0.5

1

1.5

2

2.5

0 0.2 0.4 0.6 0.8 1

f(x)

Triangular DistributionMinimum = 0Maximum = 1Most Likely = 0.1

J-84

TABLE J.17 Percent Removal of Contamination for DifferentSampling Methodsa

Removal (%)

SurfaceAdhesive

Paper SmearModified

Air

Polyethylene 70.3 56.6 10.9Glass 75.0 64.6 27.2Plexiglass 78.0 71.3 15.8Fiberboard (waxed) 53.8 44.3 10.2Fiberboard (scrubbed) 56.9 23.5 9.0Fiberboard (untreated) 73.4 23.5 6.6Formica 73.4 70.6 26.5Aluminum (painted) 70.0 50.3 24.8Asphalt floor tile (untreated) 58.6 48.5 14.6Asphalt floor tile (waxed) 74.5 74.5 30.3Concrete (unsealed) 55.5 39.5 22.0Concrete (sealed [seal and wax 1]) 62.2 59.5 24.0Concrete (sealed [seal and wax 2]) 54.8 47.7 27.2Concrete (greased) 43.5 37.5 1.32 Stainless steel 67.7 50.5 10.5

a Modified air sampler (referred to as a “smair” sampler by theauthors) causes air intake to blow across the sample surface whenthe sample head is pressed against a surface.

Source: Royster and Fish (1967); contamination was simulated bythorium dioxide dust particles approximately 1� �� concentration of about 1 � 106 particles per square centimeter.

J-85

J.4.10 Source Lifetime (also Time for Source Removal)

Definition: This parameter represents the time over which the removable part of the source is(linearly) eroded. The parameter is used in conjunction with the removable fraction of sourcematerial parameter (Section J.4.9) and the air release fraction (Section J.4.7) to obtain theemission rate of radionuclides into the indoor air.

Parameter Name: RF0 Units: Days (d) Range: > 0


Probabilistic Analysis Default Distribution: TriangularDefining Values for Distribution:Minimum: 1,000 Maximum: 100,000 Most likely: 10,000 (27.4 yr)


Discussion: The RESRAD-BUILD model considers the potential entrainment of loosecontamination from a contaminated surface to the indoor atmosphere. The entrainment rate of theloose contamination is calculated by using the “removable fraction” parameter (Section J.4.9),the “time for source removal or source lifetime” parameter (Section J.4.10), and the totalcontaminant inventory on the surface. Information on the time for source removal or sourcelifetime parameter is not directly available from the open literature; therefore, the potential rangeof this parameter was inferred on the basis of information on other, related parameters.

Different mechanisms can result in the entrainment of loose surface particles to theatmosphere. Mechanical abrasion during renovation activities would result in the highestentrainment rate in the shortest period of time. However, for normal building occupancyconditions, renovation activities were excluded from consideration.

According to the American Nuclear Society (ANS), an air release rate of 4 × 10-5/h is aconservative value for use in estimating the potential exposure resulting from release of solidpowders piled up on a heterogeneous surface under the condition of normal building ventilationflow (ANS 1998). That rate is equivalent to a lifetime of approximately 1,040 days (or2.85 years). Although the loose particles on the contaminated source are not exactly the same as apile of solid powders, the value for the free solid powders can be used to derive a lower boundinglifetime value for the loose materials.

Another suggestion by the ANS is an air release rate of 4 × 10-6/h for solid powders thatare covered with a substantial layer of debris or are constrained by indoor static conditions(ANS 1998). This rate is equivalent to a lifetime of approximately 10,000 days (27.4 yr). Theloose contaminants on a contaminated surface can be considered as being restricted by some

J-86

weak physical binding force and would, therefore, behave like the constrained solid powders.The lifetime of the constrained solid powders can be used as the most likely value for the loosecontaminants.

Erosion of the surface layer from the contaminated material can eventually occur over along period of time if there is no constant maintenance. Therefore, all the loose contaminantshave the opportunity of being released to the environment. To consider this extreme case, alifetime of 300 years (approximately 100,000 days) was assumed. The probability densityfunction is shown in Figure J.15.

Another factor that is frequently used in the literature for estimating air concentrationsfrom surface sources is the resuspension factor. The resuspension factor is not used in theRESRAD-BUILD code, but it is a quantity closely related to the source lifetime for a surfacesource. The air concentration in a one-room air quality model under equilibrium conditions for asurface source with long-lived radionuclide contamination (or for chemicals where no decay isinvolved) can be given as (derived from Equation A.28):

(J.4.10-1)

where

Q0 = ,Vabλ (J.4.10-2)

nsQ = Csurf As, (J.4.10-3)

V = AH, (J.4.10-4)

�ab = air exchange rate (1/h),

As = source area (m2),

A = area of the compartment (m2),

H = height of the compartment (m),

Csurf = surface concentration (pCi/m2),


Cf f Q

T Qn R s

n

R

=24 0

J-87

f = fraction of removed material that becomes indoor dust, and

TR = time to remove material from the source (source lifetime) (d).

When the whole floor is contaminated, the air concentration reduces to

.24 HT

CffC

abR

surfRn

λ= (J.4.10-5)

The resuspension factor, RF, under these assumptions can be given as

(J.4.10-6)

The air release fraction, f, in RESRAD-BUILD is the fraction of contaminated material removedfrom the source released into the air that is in the respirable particulate range. Assuming a surfacesource on the floor with a removable fraction of 0.1 (Section J.4.9) and an air release fraction of0.07 (Section J.4.7), the resuspension factor can be estimated from the source lifetime. A floorarea of 36 m2 (Section J.2.5), a room height of 3.7 m (Section J.2.4), and a room air exchangerate of 1.52 h-1 (Section J.2.6) were used. In this case, the source lifetime of 10,000 days isequivalent to a resuspension factor of 5 × 10-9/m.

Table J.18 gives the source lifetime (days) for different air exchange rates and heights fora fixed resuspension factor of 1 × 10-6 m-1. For these calculations, it is assumed that theremovable fraction is 1 and that the fraction that become airborne is also 1. When an airbornefraction of 1, an air exchange rate of 0.5 h-1, and a room height of 2.3 m are assumed, the sourcelifetime (in years) can be related to resuspension factor, as shown in Table J.19.

The source lifetime depends on how easily the source material can be removed and theexternal conditions to which the source is exposed (e.g., corrosion, mechanical contact, heat). Ifthe source is fixed, the removable fraction should be set to 0, so the source lifetime is immaterial.The code assumes a linear removal over time. For example, for a source with a lifetime of 1 year,50% of the removable fraction is assumed to be removed after 6 months. The code requires asource lifetime for each area, line, and point source whenever a nonzero removable fraction isentered. If the removable fraction for a source is 0, the code ignores any lifetime value entered bythe user for that source.

R =f f

T HF

R

R ba24 λ

.

J-88

FIGURE J.15 Time for Source Removal or Source Lifetime ProbabilityDensity Function

TABLE J.18 Source Lifetime (d) Variation with Air Exchange Rateand Room Height for a Fixed Resuspension Factor of 1 × 10-6 m-1

Air Exchange Rate (h-1)

Height (m) 0.2 0.5 0.8 1.0 1.5

2.5 8.3E+04 3.3E+04 2.1E+04 1.7E+04 1.1E+043.0 6.9E+04 2.8E+04 1.7E+04 1.4E+04 9.3E+036.0 3.5E+04 1.4E+04 8.7E+03 6.9E+03 4.6E+03

10.0 2.1E+04 8.3E+03 5.2E+03 4.2E+03 2.8E+03

0.0E+00

5.0E-06

1.0E-05

1.5E-05

2.0E-05

2.5E-05

0 20,000 40,000 60,000 80,000 100,000 120,000

Time for Source Removal or Source Lifetime (days)

f(x)

Triangular DistributionMinimum = 1,000 daysMaximum = 100,000 daysMost Likely = 10,000 days

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TABLE J.19 Source Lifetime (yr) andResuspension Factor for Different RemovableFractions for a House with an Air ExchangeRate of 0.5 h-1 and a 2.3-m Room Height

ResuspensionFactor (m-1)

RemovableFraction (%)

SourceLifetime (yr)

1E-08 100 10,00010 1,000

1E-06 100 10010 10

1E-04 100 110 0.1

J-90

J.4.11 Radon Release Fraction

Definition: This parameter represents the fraction of the total amount of radon produced byradium decay that escapes the surface of a contaminated material and is released to the air. Thisparameter applies to point, line, and area sources.

Parameter Name: RRF Units: Unitless Range: 0 to 1




Discussion: The radon release fraction represents the combined effect of the radon emanationcoefficient and the radon diffusion coefficient that apply to volume sources. This parameter isused by RESRAD-BUILD in conjunction with the concentrations of radium-226 and thorium-228 in a nonvolume source to calculate the release of radon-222 and radon-220, respectively, intothe room air. It is applicable only to the radon inhalation pathway. Therefore, it is only requiredas input when radionuclides that decay to radon are entered as part of an area, line, or pointsource. It is not required for a volume source. (For volume sources, see Sections J.4.19 andJ.4.20 on the radon effective diffusion coefficient and radon emanation coefficient, respectively.)

The radon release fraction is a unitless parameter ranging in value from 0 to 1. Valuesapproaching 0 indicate that the majority of the radon from radium decay is retained in the sourcematerial and is not being released to the room air. A release fraction of 1 indicates that all of theradon is being released to the room air. This parameter depends on the combined properties ofradon emanation and diffusion through the thin area, line, or point source layer. If the source issufficiently thin (e.g., area source) and there is no additional layer between the source and theroom air, diffusion may be neglected and the release fraction will approach the emanationcoefficient. If the source is inside a closed, nonporous pipe (line source) or small, sealedcontainer (point source), the radon release fraction should be set to 0.

If an area, line, or point source is selected and if that source contains a radionuclide that isa radon precursor, the user must enter a radon release fraction between 0 and 1. The precursorradionuclides are listed in Section J.4.18 on source porosity. Setting a value of 0 for the radonrelease fraction effectively suppresses the radon pathway for area, line, or point sources.

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J.4.12 Radionuclide Concentration/Activity

Definition: This parameter specifies the activity (for a point source) or activity concentration (forvolume, area, and line sources) of radionuclides distributed in a source.

Parameter Name: RNUCACT

Units: Activity (point source); Activity/m (line source); Activity/m2 (area source); Activity/g(volume source)

Range: > 0

Default Value: 1 pCi/g of Co-60


Discussion: Any of the following four units of radiological activity can be selected: (1) Ci orcurie, defined as 3.7 × 1010 disintegrations per second (dps); (2) Bq or becquerel, defined as1 dps; (3) disintegrations per second (dps); or (4) disintegrations per minute (dpm). Any standardone-character metric prefix can be used with Ci and Bq. This parameter is not eligible forprobabilistic input. The activity or concentration is assumed to be distributed homogeneouslythroughout each source, except volume sources, which may have one contaminated layer and upto four additional uncontaminated layers.

The total activity or activity concentration in a source may be estimated by performingfield measurements or by taking source samples and performing radiological analyses that areappropriate for the radionuclide(s) present in that source. Since the code assumes a uniformdistribution of radionuclides within a source, the average concentration should be estimated fromseveral measurements. If individual regions of the source differ significantly from the average(e.g., by a factor of 3 or more above or below this average), the user should consider dividing thesource region into smaller subregions with more homogeneous distribution of radionuclides.These subregions, along with their respective radionuclide concentrations, should then be enteredas separate sources in the code (see Section J.4.1 on the number of sources).

Up to 10 radionuclides per source may be considered from a list of 67 radionuclides inthe RESRAD-BUILD database. If more than 10 radionuclides are present in a single source, theuser may create two or more sources (as necessary), each with up to 10 radionuclides. Thesemultiple sources should be identical with regard to their geometric and physical characteristics(e.g., type, location, dimension, and removal fraction). The units used to enter radionuclideactivity or concentration will depend on the source type, as follows: picocuries (pCi) for pointsources, pCi per meter (m) for line sources, pCi per square meter (m2) for area sources, or pCi

J-92

per gram (g) for volume sources. The user can also select other radiological activity units asdiscussed above.

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J.4.13 Number of Regions in Volume Source

Definition: This parameter specifies the number of distinct layers in a volume source. It does notapply to area, line, or point sources.

Parameter Name: NREGI0 Units: Unitless Range: Integer value of 1 to 5

Default Value: 1


Discussion: The volume source can be split into as many as five regions along its thickness. Suchsplitting is useful if only part of the thickness of the building component (wall, floor, etc.) iscontaminated. This parameter is not eligible for probabilistic input. Up to five distinct regionsmay be assigned to each volume source. When more than one region is specified, thecontaminated region has to be identified. Only one of the regions can be specified to becontaminated. The uncontaminated regions will act as a shield for external gamma radiation onthe basis of thickness (Section J.4.15) and density (Section J.4.16) and will act as a barrier for theinhalation pathways. The number of regions is used to define possible heterogeneities in thephysical and radiological characteristics of a volume source. In cases in which the physicalcharacteristics of the source are homogeneous and the contamination is uniformly distributedthroughout the entire volume, one region should be selected. An exception to this rule should bemade for a volume source that forms a common boundary between rooms. In this case, the sourceshould be divided into two overlapping subsources, each consisting of two layers (seeSection J.4.2 on the source room). The code requires that at least one layer, but no more than fivelayers, be entered for each volume source.

If the source has more than one region, region 1 is the one that is closest to the originused to define the coordinates of the sources and the receptors. All releases from the source, otherthan those of radon, are assumed to occur from region 1. This assumption imposes a restrictionon the choice of the origin.

For cases in which heterogeneities arise from the physical properties of the source, thenumber of regions may be directly measured by taking a core sample of the source. Alternativeoptions are to refer to standard building codes or the building design specifications. For cases inwhich heterogeneities arise from nonuniform contamination across the depth of the source, therequired information can be obtained from a radiological characterization of the core samples.

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J.4.14 Contaminated Region (Volume Source)

Parameter Name: FCONT0

Definition: This parameter specifies the number of the contaminated region in a volume source.This parameter does not apply to area, line, or point sources.

Parameter Name: FCONT0 Units: Unitless Range: Integer value of 1 to 5

Default Value: 1

Window: Source Parameters → Source Details → Wall Region Parameters

Discussion: This parameter is not eligible for probabilistic input. Only one region (i.e., layer) isallowed to be contaminated per volume source. This region number may be 1, 2, 3, 4, or 5 and islimited by the number of regions that have been defined (see Section J.4.13, Number of Regionsin Volume Source). For example, in a volume source with two regions, the user may define thecontamination to be in region (or layer) 1 or 2 but is not allowed to define the contamination tobe in region 3, 4, or 5. However, multiple layers of contamination may be modeled by creatingmultiple volume sources, each occupying the same physical space. For example, assume a sourcehas three layers of contamination, each with different radionuclide concentrations. The sourcecan then be modeled as three co-located sources, each with three layers. The physicalcharacteristics of the layers within each source would be the same in all three sources. The firstcontaminated layer would be entered as region 1 of the first source, the second layer as region 2of the second source, and the third layer as region 3 of the third source.

The code requires that the user identify one of up to five layers as the contaminated layerin each volume source. The user does not enter a number but actually selects the contaminatedregion. If the number of regions is then reduced to fewer than the number of regions containingthe contamination, the user must reselect the correct region or layer; otherwise, the code assumesthe source is one layer when it runs.

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J.4.15 Source Region Thickness (Volume Source)

Parameter Name: THICK0

Definition: This parameter represents the thickness of each layer in an idealized volume source.This parameter does not apply to area, line, or point sources.

Parameter Name: THICK0 Units: cm Range: > 0


Probabilistic Analysis Default Distribution: TriangularDefining Values for Distribution:Minimum: 2.5 Maximum: 30 Most likely: 15


Discussion: RESRAD-BUILD allows consideration of a total of five distinct regions (layers) in avolume source. The contamination is in one of those regions, and the total thickness of thevolume source is the sum of the thicknesses of those regions. The code requires a sourcethickness (in centimeters) for every layer of each volume source. The source thickness dependsupon the detail of modeling desired. For example, a wall could be modeled as a single layer ormultiple layers (e.g., a sequence of paint, drywall, framing gap, drywall, and paint), with up tofive layers per source. It is highly recommended that the source thickness be obtained from directmeasurement or be estimated on the basis of the applicable building codes. The contaminatedlayer thickness and position should be based on site-specific measurement.

With the exception of sources resulting from neutron activation, most volume activity inbuildings will be limited to small areas (hot spots) or rather shallow sources. For the case ofneutron activation, volume sources could extend deep into the volume of a building structure.The thickness of building structure materials will place a limit on the potential thickness forvolume sources. Ayers et al. (1999) noted that the contamination of concrete usually results fromspills, contaminated dust, or other surficial deposition. In some instances, the contaminants maymigrate into the concrete matrix, particularly over time and under environmental stresses. Cracksand crevices may also provide routes for contaminants to spread deeper into the concrete matrix.To estimate the total contaminated volume of concrete from DOE facilities, Ayers et al. (1999)assumed contamination to a 1-in. (2.5-cm) depth and an average concrete thickness of 12 in.(30 cm) in a building. For external exposure calculations, this thickness will approximate aninfinite thickness for alpha-emitters, beta-emitters, and X-ray or low-energy photon emitters.RESRAD-BUILD uses 15 cm as the default source thickness for a volume source.

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Little information is available for the source thicknesses in actual decommissioning anddecontamination situations; therefore, on the basis of the above data, a triangular distribution isassumed for source thickness. The maximum value is assumed to be 30 cm, the minimum valueis chosen as 2.5 cm, and the most likely value is 15 cm. Figure J.16 presents the probabilitydensity function for the source thickness.

FIGURE J.16 Source Thickness Probability Density Function

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0 5 10 15 20 25 30 35 40

Source Thickness, Volume Source (cm)

f(x)

Triangular DistributionMinimum = 2.5 cmMaximum = 30 cmMost Likely = 15 cm

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J.4.16 Source Density (Volume Source)

Definition: The source density parameter represents the bulk density of each cylindrical layer(region) in an idealized volume source. This parameter does not apply to area, line, or pointsources.

Parameter Name: DENSI0 Units: g/cm3 Range: 0–22.5


Probabilistic Analysis Default Distribution: Uniform (only allowed for concrete)Defining Values for Distribution:Minimum: 2.2 Maximum: 2.6


Discussion: The source density parameter is used to calculate the total amount of radionuclidesin the source volume, and it affects the external pathway doses. In the RESRAD-BUILD code,the volume source can be defined with up to five distinct parallel regions (or layers) locatedalong the direction parallel to the partition, each consisting of homogeneous and isotropicmaterials. RESRAD-BUILD allows the following eight materials: concrete, water, aluminum,iron, lead, copper, tungsten, and uranium. Each source layer is defined by its physical properties,such as thickness, density, porosity, radon effective diffusion coefficient, radon emanationfraction, and erosion rate.

As is the case for shield density, the source density will never exceed 22.5 grams percubic centimeter (g/cm3). Table J.20 lists the density range (if appropriate) or a single value ofdensity for the RESRAD-BUILD materials that have a narrow range of density (except concrete).The table lists a range for cast iron and a single value of density for each of the other materials.The values are taken from The Health Physics and Radiological Health Handbook (Shleien1992) and from the CRC Handbook of Chemistry and Physics (Lide 1998) (for cast iron,uranium, and tungsten). Table J.21 provides the concrete density from three different sources:The Health Physics and Radiological Health Handbook (Shleien 1992), Properties of Concrete(Neville 1996), and Standard Handbook for Civil Engineers (Merritt et al. 1995). The value usedin the code is for ordinary concrete. If the type of concrete is known, a uniform distributionbetween the given range for a known concrete type can be used. The probability density functionfor the concrete source density is shown in Figure J.17.

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TABLE J.20 Density of Source Materials(except concrete) Allowed in RESRAD-BUILD

MaterialDensity Range

(g/cm3)Normal Density

(g/cm3)

Aluminum -a 2.7 Copper - 8.96 Lead - 11.35 Steel - 7.8 Cast iron 7.0�7.4Water - 1.0 Tungsten - 19.3 Uranium - 19.1 Iron - 7.87

a A dash indicates that no data were available.

Sources: Shleien (1992); Lide (1998).

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TABLE J.21 Source (Concrete) Density from Various Sources

Concrete Density (g/cm3)

AggregateShleien(1992)

Neville(1996)

Merritt et al.(1995)

Ordinary (silicacious) or normal weight 2.2–2.4 2.2–2.6 2.3Heavy weight -a - 2.4–6.15Limonite (goethite, hyd. Fe2O3) 2.6–3.7 - -Ilmenite (nat. FeTiO3) 2.9–3.9 - -Magnetite (nat. Fe3O4) 2.9–4.0 - -Limonite and magnetite - - 3.35–3.59Iron (shot, punchings, etc.) or steel 4.0–6.0 - 4.0–4.61Barite 3.0–3.8 - 3.72Lightweight - 0.3–1.85 0.55–1.85Pumice - 0.8–1.8 1.45–1.6Scoria - 1.0–1.85 1.45–1.75Expanded clay and shale - 1.4–1.8 -Vermiculite - 0.3–0.8 0.55–1.2Perlite - 0.4–1.0 0.8–1.3Clinker - 1.1–1.4 -Cinders without sand - - 1.36Cinders with sand - - 1.75–1.85Shale or clay - - 1.45–1.75Cellular - 0.36–1.55 -No-fines - 1.6–2.0 1.68–1.8No-fines with lightweight aggregate - 0.64–higher -Nailing - 0.65–1.6 -Foam - - 0.3–1.75

a A dash indicates that no data were available.

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FIGURE J.17 Concrete Source Density Probability Distribution Function

0

0.5

1

1.5

2

2.5

3

2 2.2 2.4 2.6 2.8 3

Source Density (g/cm3)

f(x)

Uniform Distribution

Minimum = 2.2 g/cm3

Maximum = 2.6 g/cm3

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J.4.17 Source Erosion Rate (Volume Source)

Parameter Name: EROS0

Definition: The source erosion rate parameter represents the amount of contaminated material(expressed as the thickness of the layer [distance perpendicular to the contaminated surface])removed per unit of time.

Parameter Name: EROS0 Units: cm/d Range: ≥ 0

Deterministic Analysis Default Value: 2.4 × 10-8

Probabilistic Analysis Default Distribution: TriangularDefining Values for Distribution:Minimum: 0.0 Maximum: 5.6 × 10-7 Most likely: 0.0


Discussion: This parameter does not apply to area, line, or point sources. The source erosion rateis used in determining the amount of the source released into the air, the amount of the sourceremaining to contribute to external exposure, and the amount of material through which theradon must diffuse. Also, at each evaluation time, the erosion rates of all the layers are used toidentify the exposed layer.

The source erosion rate is highly dependent on the location of the contamination. In abuilding occupancy scenario, contamination on walls could remain indefinitely if located in little-used areas not subject to periodic washing or cleaning. Furthermore, such residual wallcontamination could have been covered with paint or another type of sealant during priorremediation or general maintenance activities. In addition, little or no wear can be expected forsome floor areas for the same reasons. At the other extreme are contaminated floor areas subjectto heavy foot traffic or vehicle traffic, such as in warehousing operations. However, such areasare usually covered (carpet or tile), sealed, or waxed on a periodic basis, thus reducing thepotential for erosion.

A triangular distribution was selected to represent the source erosion rate. A value of 0was chosen for both the minimum and most likely values because contamination on both wallsand floors in little-used areas can be expected to remain in place indefinitely. Even high-use areasmay not experience erosion if they remain protected by paint or sealant. Under normal occupancyconditions (not remedial activities), a maximum value is expected as a result of traffic over floorareas. Contaminated wood, concrete, and (possibly) ceramic tile are expected to be the primaryflooring materials affected. Contaminated carpet would be expected to have been removed by

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remedial activities. However, aside from studies on abrasion, little information is available in thegeneral literature on normal wear of concrete or wood surfaces over extended periods of time.

A rough approximation for the maximum value can be obtained by considering that anyeroded materials would become airborne for at least short periods of time. A conservativeassumption was made that all airborne indoor particulate matter is a result of erosion of the floorsurface. Typically, outdoor air is a significant source of indoor air particulate concentrations(Wallace 1996), but this contribution was not considered. The erosion rate of a concrete floorwas estimated to maintain an average particulate air concentration of 100� ��3 with a room airexchange rate of 1.52/h (Section J.2.6). A floor area of 36 m2 (Section J.2.5), a room height of3.7 m (Section J.2.4, used to estimate the room volume), and a concrete density of 2.4 g/cm3

(Section J.4.16) were used. The estimated erosion rate was 5.6 × 10-7 cm/d. Figure J.18 showsthe probability density function used for the source erosion rate.

In the case of renovation or remedial actions, the source erosion rate can be quite high.For example, thin-volume sources in wood or concrete could be removed in seconds with powersanders or sandblasting techniques. Other examples include the complete removal of wood,carpet, or drywall sections within seconds to minutes. For such a scenario, the user can inputvalues appropriate to the contaminated source and removal technique under consideration.

In the case of contaminated metal sources, the database generated by the National Bureauof Standards (NBS; currently the National Institute for Standards and Technology) can providesome information on carbon and stainless steels (Sullivan 1993). In a study conducted over aperiod of 17 years in 47 different soils, carbon steel’s uniform erosion rates ranged from 2 × 10-6

to 5 × 10-5 cm/d, with a mean value of 1 × 10-5 cm/d (Romanoff 1957). Another other study wasconducted over a period of 14 years in 15 soils for 304 and 316 stainless steels. The erosion ratesfor 304 stainless steel ranged from 4.7 × 10-8 to 3.0 × 10-10 cm/d, with a mean value of1.4 × 10-8 cm/d; for 316 stainless steel, the range was from 1.6 × 10-8 to 7.7 × 10-11 cm/d, with amean value of 3.6 × 10-9 cm/d (Gerhold et al. 1981). It was also observed that the corrosion ratestypically decreased over time. Because these corrosion rates were obtained while the steel was incontact with soil, lower rates might be expected in less corrosive environments. Thus, these rates(used as erosion rates) are near the most likely value of 0 for the source erosion rate shown inFigure J.18.

In summary, the erosion rate depends on how easily the source material can be removedand the external conditions to which it is exposed. If the layer is not removable, the erosion rateshould be set to zero. The code requires a source erosion rate in centimeters per day (cm/d) forevery layer of each volume source.

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FIGURE J.18 Source Erosion Rate Probability Density Function

0.0E+00

5.0E+05

1.0E+06

1.5E+06

2.0E+06

2.5E+06

3.0E+06

3.5E+06

4.0E+06

0.0E+00 1.0E-07 2.0E-07 3.0E-07 4.0E-07 5.0E-07 6.0E-07

Source Erosion Rate, Volume Source (cm/d)

f(x)

Triangular DistributionMinimum = 0 cm/d

Maximum = 5.6 × 10-7 cm/dMost Likely = 0 cm/d

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J.4.18 Source Porosity

Definition: The source porosity is the ratio of the pore volume to the total volume of arepresentative sample of the source material.

Parameter Name: POROS0 Units: Unitless Range: >0 to <1


Probabilistic Analysis Default Distribution (only allowed for concrete): uniformDefining Values for Distribution:Minimum: 0.04 Maximum: 0.25


Discussion: The source porosity parameter is used in RESRAD-BUILD to calculate the diffusionof radon and tritium from a volume source and is applicable to the tritium inhalation and theradon inhalation pathways. This parameter is only required as input if a tritium volume source isselected or if radon (radon-220 or radon-222) precursors are entered as part of the volume source.It is not required for area, line, or point sources. Precursor radionuclides are listed below:

• Radon-220 precursors: Cf-252, Cm-244, Cm-248, Pu-244, Pu-240, U-236,U-232, Th-232, Th-228, and Ra-228

• Radon-222 precursors: Pu-242, Pu-238, U-238, U-234, Th-230, and Ra-226

The porosity of each of up to five layers in each volume source containing one or more radonprecursors must be entered.

Porosity may be reported as a decimal fraction or as a percentage. Input to the RESRAD-BUILD code is as a decimal fraction. A value of 0 represents a material that is completely solid,without any void spaces. On the other extreme, a porosity approaching 1 represents a materialthat is made up mostly of void spaces. Building materials such as concrete, brick, or rocktypically have porosities up to 0.3.

Widespread variations in concrete porosity occur because of the differences in theaggregates used, water/cement ratios in the cement paste, and curing conditions. Cement paste inconcrete occupies from 23 to 36% of the total volume (Culot et al. 1976), sand 25 to 30%, andaggregates the remainder. Overall porosity of concrete depends on the porosity of the cementpaste as well as of the aggregates. The porosity of concrete was found to range from 0.05 to 0.25(Culot et al. 1976).

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The porosity estimated for a concrete structure made of Portland cement was found tovary from 0.04 to 0.20 (Frankowski et al. 1997). Table J.22 gives the bulk density and porosity ofthe rocks commonly used as building materials (Bever 1986). Other materials, such as wood,particle board, and drywall, will have porosities of around 0.5. Materials used for thermalinsulation tend to have a very high air content, with porosities approaching 1. Material porosity isinversely correlated with material density; low-porosity materials have higher densities thanporous materials.

On the basis of the definition of porosity, the porosity of a material could be evaluated bydirectly measuring the pore volume and the total volume. The American Society for Testing andMaterials (ASTM) has established a standard procedure (B-276) for cemented carbide to rate�� !Type�"�� #�$��%&� �!��'��ering porosity developed by thepresence of free carbon). Similarly, the ASTM has developed standard test methods for porosityof metal structure parts, and porosity tests for electrodeposits and related metallic coatings(http://www.astm.org/sitemap.html).

For generic applications, a uniform distribution from 0.04 to 0.25 is suggested for thesource porosity for concrete. The minimum and maximum values were those reported byFrankowski et al. (1997) and Culot et al. (1976), respectively. The probability density function isshown in Figure J.19.

A material’s porosity could be evaluated by directly measuring its pore volume (Vp) andtotal volume (Vt). The total volume is easily obtained by measuring the total volume of thesample. In principle, the pore volume could be evaluated directly by measuring the volume ofwater needed to completely saturate the sample. In practice, this measurement is very difficult tomake. Porosity is usually evaluated indirectly by using the expression p = 1 − (Vs/Vt) = 1 −(ρb/ρs), where p is the porosity as a decimal fraction, Vs is volume of the solid components, Vt isthe total volume, ρb is the dry bulk density of the sample, and ρs is the density of the solidcomponent (U.S. Department of the Army 1970, Appendix II; Danielson and Sutherland 1986). Ifthe density of the solid component is unknown, it may be estimated by crushing or grinding thesample to eliminate most of the void spaces.

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TABLE J.22 Bulk Density andPorosity of Rocks Commonly Usedas Building Materials

RockBulk Density

(g/cm3)Porosity

(%)

Granite 2.6-2.7 0.5-1.5Basalt 2.8-2.9 0.1-1.0Sandstone 2.0-2.6 0.5-25.0Limestone 2.2-2.6 0.5-20.0Gneiss 2.9-3.0 0.5-1.5Marble 2.6-2.7 0.5-2.0

Source: Bever (1986).

FIGURE J.19 Concrete Source Porosity Probability Density Function

0

1

2

3

4

5

6

7

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4

Source Porosity

f(x)

Uniform DistributionMinimum = 0.04Maximum = 0.25

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J.4.19 Radon Effective Diffusion Coefficient

Definition: This parameter represents the diffusivity of radon in air or materials.

Parameter Name: EFDIF0 Units: m2/s Range: > 0 to 1.1 × 10-5 m2/s

Deterministic Analysis Default Value: 2 × 10-6

Probabilistic Analysis Default Distribution: LoguniformDefining Values for Distribution:Minimum: 6 × 10-10 Maximum: 7.2 × 10-6


Discussion: In air, the diffusion of radon gas atoms results from a net migration of radon gastoward the direction of its decreasing concentration. The diffusion of radon in open air can bedescribed by Fick’s law, which states that the flux density of the diffusing substance is linearlyproportional to its concentration gradient. The diffusion coefficient of radon in air can beexpressed as the ratio of the flux and the concentration gradient. In porous materials, the radoneffective diffusion coefficient is defined as the ratio of the diffusive flux density of radon acrossthe pore area to the gradient of the radon concentration in the pore or interstitial space. Thisparameter is used by RESRAD-BUILD to calculate the diffusion of radon from a volume sourceand is only applicable to the radon inhalation pathway. Therefore, it is only required as inputwhen radionuclides that decay to radon are entered as part of a volume source. It is not requiredfor area, line, or point sources. Additional information on the radon effective diffusioncoefficient (De) can be found in the RESRAD Data Collection Handbook (Yu et al. 1993).

The effective radon diffusion coefficient varies over a wide range, depending on thediffusion medium. The upper limit of De is given by the diffusion coefficient in open air, whichis about 1.1 × 10-5 m2/s (Kalkwarf et al. 1982). At the lower extreme, some low-permeabilitymaterials may have diffusion coefficients as low as 10-10 m2/s.

Radon diffusion decreases with decreasing porosity. Diffusion in brick and concrete istypically 1 to 2 orders of magnitude lower than that found in soils because of the decrease inporosity (Nero and Nazaroff 1984). The observed range of variation of De in concrete is from8 × 10-9 to 4 × 10-7 m2/s (Nazaroff et al. 1988). The effective diffusion coefficient in otherbuilding materials ranges from 8 × 10-8 to 3 × 10-7 m2/s for brick and from 1 × 10-6 to4 × 10-6 m2/s for gypsum (drywall). Radon diffusion also decreases with an increase involumetric water content, varying by as much as three orders of magnitude when the dry weightpercent moisture is taken from <1% to about 18% (Rogers et al. 1984). The diffusion coefficientis also affected to a lesser degree by particle shape and size; packing; and changes in thecomposition, temperature, and pressure of the gas-filled pore space and those for the liquid

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occupying the remaining pore volume. Further information can be found in Stranden and Berteg(1980) and Rogers and Nielson (1991). In general, the effective diffusion coefficient approachesits upper limit for fibrous insulation material and its lower limit for relatively impermeablematerials or membranes, such as metals or sealants.

The diffusion coefficient (or diffusivity) of radon in materials can be measured by bothfield and laboratory experiments. In either case, the experimental evaluation of diffusivityconsists in determining the numerical value of the coefficient appearing in Fick’s equation.Because of the difficulty in implementing field methods, laboratory methods are generally usedto determine the radon diffusivity in porous media. The methods may be separated into twodistinct groups: the steady-state diffusion method and the transient diffusion method (Nielsonet al. 1982). The methods discussed apply specifically to soils but may be extended to otherporous materials.

A steady-state diffusion method for determining De in uncontaminated (no radon source)materials was implemented by Silker and Kalkwarf (Silker 1981; Silker and Kalkwarf 1983) onthe basis of theoretical developments by Cohen (1979). The apparatus used in this methodconsists of a column of test material of known depth, which is sealed at one end to an airchamber of known volume containing a radon source with a known and constant strength. Theother end of the test column is kept open. As a boundary condition for this system, it is assumedthat in a steady-state situation, the effective flux density of radon activity at the bottom of thecolumn is constant and uniquely dependent on the strength of the radon source and the geometryof the system. Also, the radon activity concentration at the open end of the column is assumed tobe negligible. Therefore, by selecting the size (i.e., thickness) of the test sample, determining theeffective flux density on the basis of the strength of the radon source and the column diameter,and making several measurements of the radon concentration, Fick’s equation in one dimensionmay be solved.

The samples used in the determination of De typically have a cylindrical shape, with aheight of 10 cm and an inner diameter of 14 cm. After equilibration, the steady-state radonconcentration in the bottom chamber is determined by several measurements taken over a 7- to14-day period. Each measurement consists of withdrawing about 5 cm3 of gas from a typical800-cm3 bottom chamber and determining the radon concentration by using either a scintillationflask technique (such as a Lucas cell) or charcoal absorption and gamma-ray spectrometry (Silker1981).

In RESRAD-BUILD, each time a volume source is selected, if the source contains aradionuclide that is a radon precursor, the user must enter a radon effective diffusion coefficientin units of square meters per second (m2/s). These precursor radionuclides are listed inSection J.4.18 on source porosity. Effective diffusion coefficients are material dependent andmust be entered for each layer of each volume source considered. Setting a value of 0 for theradon diffusion coefficient in any uncontaminated layer of a volume source effectivelysuppresses the flux of radon through that layer until that layer has eroded, thereby rendering the

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input of other radon-related parameters for that layer inconsequential. Figure J.20 presents theprobability density function for the radon effective diffusion coefficient.

FIGURE J.20 Radon Effective Diffusion Coefficient (m2/s)

1.E+00

1.E+01

1.E+02

1.E+03

1.E+04

1.E+05

1.E+06

1.E+07

1.E+08

1.E+09

1.E-11 1.E-10 1.E-09 1.E-08 1.E-07 1.E-06 1.E-05 1.E-04

f(x)


Minimum = 6.0 � 10-10 m2/s

Maximum = 7.2 � 10-6 m2/s

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J.4.20 Radon Emanation Fraction

Definition: This parameter represents the fraction of the total amount of radon produced byradium decay that escapes the matrix of the contaminated material and gets into the pores of themedium.

Parameter Name: EMANA0 Units: unitless Range: 0 to 1


Probabilistic Analysis Default Distribution: loguniformDefining Values for Distribution:

Minimum: 0.002 Maximum: 0.83


Discussion: This parameter is also called the emanating power, emanation coefficient, releaseratio, and escape-to-production ratio. The radon emanation fraction is used by RESRAD-BUILDin conjunction with the concentration of radium-226 and radium-228 to calculate the release ofradon-222 and radon-220, respectively, into the pore space of a volume source and is onlyapplicable to the radon inhalation pathway. It is only required as input when radionuclides thatdecay to radon are entered as part of a volume source. It is not required for area, line, or pointsources (see Section J.4.11, Radon Release Fraction). Additional information on the radonemanation fraction can be found in the RESRAD Data Collection Handbook (Yu et al. 1993).

The radon emanation fraction is a unitless parameter ranging in value from 0 to 1. Valuesapproaching 0 indicate that the majority of the radon is retained in the matrix of the material andis not being released to the pore space. An emanation fraction approaching 1 indicates that mostof the generated radon is being released to the pore spaces inside the contaminated material. Thevalues of the radon emanation fraction have been measured mostly for soils. Experimentalmeasurements conducted by various investigators have been reported in Nazaroff et al. (1988);they show variations in the radon emanation fraction ranging from 0.02 to 0.72, with averagevalues ranging from 0.12 to 0.30.

The radon emanation fraction varies with total porosity and the volumetric water content.More pore space (larger pore size) in a sample increases the likelihood of the radon recoilterminating outside of a soil grain. An increased water content also increases the probability of aradon recoil terminating in a pore space because of the damping effect of the water on the radonprogression (Nero and Nazaroff 1984). The damping effect generally accounts for less than anorder of magnitude change in the emanation fraction with an increase in water content (Strongand Levins 1982). In contrast, larger grain size (longer path to an opening) decreases the

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probability of the radon’s escaping to the pore areas. The distribution of the parent radium in thegrains is therefore an influencing factor if the distribution is uneven. The majority of informationavailable is for the more common isotope Rn-222. The emanation fraction for Rn-220 has beenstudied only to a limited extent. Megumi and Mamuro (1974) studied the differences (from thedifferent recoil energies) between Rn-220 and Rn-222 in soil.

Additional information on the radon emanation fraction can be found in documents byTanner (1964, 1980); Barretto et al. (1972); Pensko et al. (1972); Wilkening (1974); Periera(1980); Ingersoll (1983); Schery et al. (1984); Damkjaer and Korsbech (1985); Van der Lugt andScholten (1985); Schery and Whittlestone (1989); Rogers and Nielson (1991); Markkanen andArvela (1992); and Rood et al. (1998).

The methodology for measuring the radon emanation fraction of a porous materialcontaminated with radium consists basically of measuring the radon concentration of the airinside a sealed accumulation chamber in which the sample of contaminated material has been leftfor a period of time (about 4 days) until the radon concentration has reached equilibrium. Adetailed description of a variation of this method is presented in Strong and Levins (1982). Theirexperimental apparatus consisted of an ingrowth (accumulation) chamber, a sampling cylinder, adiaphragm pump, a scintillation cell, and supporting electronics for the radiation measurement.

If a volume source is selected and the source contains a radionuclide that is a radonprecursor, the user must enter a radon emanation fraction. The precursor radionuclides are listedin Section J.4.18 on source porosity. Different emanation fractions may be entered for radon-222and radon-220 within the same source. Emanation fraction must be entered for each volumesource considered, but only for the contaminated layer of a multilayer source. Setting a value of 0for the radon emanation fraction effectively suppresses the radon pathway, thereby rendering theinput of other radon-related parameters inconsequential. Figure J.21 presents the probabilitydensity function for the radon emanation fraction.

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FIGURE J.21 Radon Emanation Fraction

1.E-01

1.E+00

1.E+01

1.E+02

1.E-03 1.E-02 1.E-01 1.E+00

f(x)

Loguniform DistributionMinimum = 0.002 Maximum = 0.83

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J.4.21 Source Material

Definition: This parameter specifies the material that composes the volume source.

Parameter Name: MTLS Units: Unitless

Range: Concrete, water, aluminum, iron, copper, tungsten, lead, or uranium

Default Value: concrete


Discussion: The source material determines the attenuation cross section used in calculating theexternal dose. This parameter is only required for a volume source. This parameter is not eligiblefor probabilistic input and is important only for the external pathway.

The user can select among eight source materials: (1) concrete, (2) water, (3) aluminum,(4) iron, (5) copper, (6) tungsten, (7) lead, and (8) uranium. This parameter can be determinedfrom direct inspection, standard building codes, and/or building design specifications.

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J.4.22 References

American Nuclear Society, 1998, Airborne Release Fractions at Non-Reactor Facilities, anAmerican National Standard, ANSI/ANS-5.10-1998, prepared by the Standards CommitteeWorking Group ANS-5.10, American Nuclear Society, LaGrange Park, Ill.

ANS: See American Nuclear Society.

Ayers, K.W. et al., 1999, Reuse of Concrete from Contaminated Structures, prepared byDepartment of Civil and Environmental Engineering, Vanderbilt University, Nashville, Tenn.,for the U.S. Department of Energy, Office of Science and Technology, Washington, D.C.

Barretto, P.M.C., et al., 1972, “Physical Characteristics of Radon-222 Emanation from Rocks,Soils and Minerals: Its Relation to Temperature and Alpha Dose,” p. 731 in J.A.S. Adams et al.(editors), Natural Radiation Environment II, National Technical Information Service,Springfield, Va.

Bever, M.B. (editor-in-chief), 1986, Encyclopedia of Materials Science and Engineering, Vol. 5on O–Q, The MIT Press, Cambridge, Mass.

Brunskill, R.T., 1967, “The Relationship between Surface and Airborne Contamination,”pp. 93–105 in B.R. Fish (editor), Surface Contamination, Pergamon Press, New York, N.Y.

Cohen, B.L., 1979, “Methods for Predicting the Effectiveness of Uranium Mill Tailings Covers,”Nuclear Instrumentation and Methods 164:595–599.

Culot, M.J.V., 1976, “Effective Diffusion Coefficient of Radon in Concrete: Theory and Methodfor Field Measurement,” Health Physics 30:263–270.

Damkjaer, A., and U. Korsbech, 1985, “Measurement of the Emanation of Radon-222 fromDanish Soils,” The Science of the Total Environment 45:343–350.

Danielson, R.E., and P.L. Sutherland, 1986, “Porosity,” pp. 443-462 in A. Klute (editor),Methods of Soil Analysis, Part 1: Physical and Mineralogical Methods, 2nd ed., AmericanSociety of Agronomy, Inc., and Soil Science Society of America, Madison, Wis.

DOE: See U.S. Department of Energy.

Frame, P.W., and E.W. Abelquist, 1999, “Use of Smears for Assessing RemovableContamination,” Health Physics 76(5):S57–S66.

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Frankowski, Z., et al., 1997, “Properties of the Concrete from 80-Year-Old Structures ofFacilities in the Radioactive Waste Repository,” in Proceedings of the U.S. Department ofEnergy, Low-Level Radioactive Waste Management 18th Conference, May 20-22, Salt Lake City,Utah.

Gerhold, W.F., et al., 1981, The Corrosion Behavior of Selected Stainless Steels in SoilEnvironments, NBS1R81-2228, National Bureau of Standards.

Ingersoll, J.G., 1983, “A Survey of Radionuclide Contents and Radon Emanation Rates inBuilding Materials Used in the U.S.,” Health Physics 45:363–368.

International Organization for Standardization, 1988, Evaluation of Surface Contamination-Part 1: Beta Emitters and Alpha Emitters, ISO-7503-1, International Organization forStandardization, Geneva, Switzerland.

ISO: See International Organization for Standardization.

Jones, I.S., and S.F. Pond, 1967, “Some Experiments to Determine the Resuspension Factor ofPlutonium from Various Surfaces,” pp. 83–92 in B.R. Fish (editor), Surface Contamination,Pergamon Press, New York, N.Y.

Jung, H., et al., 2001, “Consistency and Efficiency of Standard Swipe Procedures Taken onSlightly Radioactive Contaminated Metal Surfaces,” Operational Radiation Safety (Supplementto Health Physics) 80:S80−S88.

Kalkwarf, D.R., et al., 1982, Comparison of Radon Diffusion Coefficients Measured byTransient-Diffusion and Steady-State Laboratory Methods, NUREG/CR-2875, PNL-4370,prepared by Pacific Northwest Laboratory and Rogers & Associates Engineering Corporation forthe U.S. Nuclear Regulatory Commission, Washington, D.C.

Lide, D.R. (editor-in-chief), 1998, CRC Handbook of Chemistry and Physics, 79th ed., CRCPress, Boca Raton, Fla.

Markkanen, M., and H. Arvela, 1992, “Radon Emanation from Soils,” Radiation ProtectionDosimetry 45:269-272.

Megumi, K., and T. Mamuro, 1974, “Emanation and Exhalation of Radon and Thoron Gasesfrom Soil Particles,” Journal of Geophysical Research 79:3357–3360.

Merritt, F.S., et al. (editors), 1995, “Construction Materials,” Section 5 of Standard Handbookfor Civil Engineers, McGraw-Hill, New York, N.Y.

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Nazaroff, W.W., et al., 1988, “Soils as a Source of Indoor Radon: Generation, Migration, andEntry,” in W.W. Nazaroff and A.V. Nero (editors), Radon and Its Decay Products in Indoor Air,John Wiley and Sons, New York, N.Y.

Nero, A.V., and W.W. Nazaroff, 1984, “Characterizing the Source of Radon Indoors,” RadiationProtection and Dosimetry 7:23–39.

Neville, A.M., 1996, Properties of Concrete, 4th Ed., John Wiley & Sons, Ltd., Brisbane,Australia.

Nielson, K.K., et al., 1982, Comparison of Radon Diffusion Coefficients Measured by Transient-Diffusion and Steady-State Laboratory Methods, NUREG/CR-2875, U.S. Nuclear RegulatoryCommission, Washington, D.C.

NRC: See U.S. Nuclear Regulatory Commission.

Pensko, J., et al., 1972, “Emanating Power of Radon-222 Measured in Building Materials,”p. 1407 in J.A.S. Adams et al. (editors), Natural Radiation Environment II, National TechnicalInformation Service, Springfield, Va.

Periera, E.B., 1980, “Reconnaissance of Radon Emanation Power of Pocos de Caldas, Brazil,Uranium Ore and Associated Rocks,” p. 117 in T.F. Gesell and W.M. Lowder (editors), NaturalRadiation Environment III, National Technical Information Service, Springfield, Va.

Rogers, V.C., and K.K. Nielson, 1991, “Multiphase Radon Generation and Transport in PorousMaterials,” Health Physics 60:807–815.

Rogers, V.C., et al., 1984, Radon Attenuation Handbook for Uranium Mill Tailings CoverDesign, NUREG/CR-3533, PNL-4878, prepared by Rogers & Associates EngineeringCorporation and Pacific Northwest Laboratory for the U.S. Nuclear Regulatory Commission,Washington, D.C.

Romanoff, 1957, Underground Corrosion, Circular 579, National Bureau of Standards.

Rood et al., 1998, “Measurement of Rn-222 Flux, Rn-222 Emanation, and Ra-226, -228Concentration from Injection Well Pipe Scale,” Health Physics 75:187–192.

Royster, Jr., G.W., and B.R. Fish, 1967, “Techniques for Assessing ‘Removable’ SurfaceContamination,” pp. 201–207 in B.R. Fish (editor), Surface Contamination, Pergamon Press,New York, N.Y.

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Sansone, E.B., 1987, “Redispersion of Indoor Surface Contamination,” in Vol. 1 of K.L. Mittal(editor), Treatise on Clean Surface Technology, Plenum Press, New York, N.Y.

Schery, S.D., and S. Whittlestone, 1989, “Desorption of Radon at the Earth’s Surface,” Journalof Geophysical Research 94:18297–18303.

Schery, S.D., et al., 1984, “Factors Affecting Exhalation of Radon from a Gravelly Sandy Loam,”Journal of Geophysical Research 89:7299–7309.

Shleien, B. (editor), 1992, The Health Physics and Radiological Health Handbook, Rev. Ed.,Scinta, Inc., Silver Spring, Md.

Silker, W.B., 1981, A Radon Attenuation Test Facility, NUREG/CR-2243, U.S. NuclearRegulatory Commission, Washington, D.C.

Silker, W.B., and D.R. Kalkwarf, 1983, Radon Diffusion in Candidate Soils for CoveringUranium Mill Tailings, NUREG/CR-2924, PNL-4434, prepared by Pacific NorthwestLaboratory, Richland, Wash., for U.S. Nuclear Regulatory Commission, Washington, D.C.

Stranden, E., and L. Berteg, 1980, “Radon in Dwellings and Influencing Factors,” Health Physics39:275–284.

Strong, K.P., and D.M. Levins, 1982, “Effect of Moisture Content on Radon Emanation fromUranium Ore and Tailings,” Health Physics 42:27–32.

Sullivan, T.M., 1993, Disposal Unit Source Term (DUST) Data Input Guide, NUREG/CR-6041,BNL-NUREG-52375, prepared by Brookhaven National Laboratory, Upton, N.Y., for the Officeof Nuclear Material Safety and Safeguards, U.S. Nuclear Regulatory Commission, Washington,D.C.

Tanner, A.B., 1964, “Radon Migration in the Ground: A Review,” p. 161 in J.A.S. Adams andW.M. Lowder (editors), Natural Radiation Environment, University of Chicago Press,Chicago, Ill.

Tanner, A.B., 1980, “Radon Migration in the Ground: A Supplementary Review,” p. 5 inT.F. Gesell and W.M. Lowder (editors), Natural Radiation Environment III, National TechnicalInformation Service, Springfield, Va.

U.S. Department of the Army, 1970, Engineering and Design: Laboratory Soils Testing, EM1110-2-1906, U.S. Army Corps of Engineers, Washington, D.C.

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U.S. Department of Energy, 1994a, DOE Handbook, Airborne Release Fractions/Rates andRespirable Fractions for Nonreactor Nuclear Facilities, Volume 1 – Analysis of ExperimentalData, DOE-HDBK-3010-94, U.S. Department of Energy, Washington, D.C., Dec.

U.S. Department of Energy, 1994b, Radiological Control Manual, Rev. 1, DOE/EH-0256T,U.S. Department of Energy, Washington, D.C.

U.S. Nuclear Regulatory Commission, 1979a, “Health Physics Surveys for Byproduct Materialsat NRC-licensed Processing and Manufacturing Plants,” Regulatory Guide 8.21,Washington, D.C.

U.S. Nuclear Regulatory Commission, 1979b, “Radiation Safety Surveys at MedicalInstitutions,” Regulatory Guide 8.23, Washington, D.C.

U.S. Nuclear Regulatory Commission, 2000, NMSS Decommissioning Standard Review Plan,NUREG-1727, Division of Waste Management, Office of Nuclear Material Safety andSafeguards, Washington, D.C.

Van der Lugt, G., and L.C. Scholten, 1985, “Radon Emanation from Concrete and the Influenceof Using Flyash in Cement,” The Science of the Total Environment 45:143–150.

Wallace, L., 1996, “Indoor Particles: A Review,” J. Air & Waste Manage. Assoc. 46:98–126.

Weber, J., 1966, in Proceedings of the International Symposium on the Radiological Protectionof the Worker by the Design and Control of His Environment, Society for RadiologicalProtection, Bournemouth, England, April 18-22.

Wilkening, M.H., 1974, “Radon-222 from the Island of Hawaii: Deep Soils Are More Importantthan Lava Fields or Volcanoes,” Science 183:413–415.

Yu, C., et al., 1993, Data Collection Handbook to Support Modeling the Impacts of RadioactiveMaterial in Soil, ANL/EAIS-8, Argonne National Laboratory, Argonne, Ill.

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J.5 SHIELDING PARAMETERS

J.5.1 Shielding Thickness

Definition: This parameter represents the effective thickness of shielding between a source andreceptor pair.

Parameter Name: DSTH Units: cm Range: ≥ 0


Probabilistic Analysis Default Distribution: TriangularDefining Values for Distribution:Minimum: 0 Maximum: 30 Most likely: 0

Window: Shielding Parameters

Discussion: The shielding thickness parameter is used in determining the attenuation of directexternal radiation from each source to each receptor. Shielding thickness only affects the externalexposure pathway. For situations in which only air is present between the source and receptor,the shielding thickness is 0. The RESRAD-BUILD code requires the shielding thickness forevery source and receptor pair (e.g., if there were 4 sources and 6 receptors, the code wouldrequire 24 [6 × 4] shielding thickness input values). The same shielding object might be assigneddifferent thicknesses for different source-receptor pairs because of geometry considerations. It ishighly recommended that the shielding thickness value be obtained from a direct measurementbased on the site-specific condition. For example, to calculate dose for a receptor in a room otherthan the room in which the source is located, a shielding thickness equivalent to the wallthickness should be assumed.

Floor and wall thicknesses vary depending on the type of building and type ofconstruction. To estimate the total contaminated volume of concrete from DOE facilities, Ayerset al. (1999) assumed an average concrete thickness of 12 in. (30 cm) in a building. For externalexposure calculations, this thickness approximates an infinite thickness for alpha-emitters,beta-emitters, and X-ray or low-energy photon emitters. A shielding thickness of 30 cm wouldreduce the dose significantly from the external exposure pathway for all radionuclides, includinghigh-energy gamma emitters.

Little information is available for the shielding thicknesses in actual D&D situations;therefore, a triangular distribution is assumed. The maximum value is assumed to be 30 cm, theminimum value is chosen as 0 cm, and the most likely value also is chosen to be 0 cm (this

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assumption would yield the most conservative dose results for the external exposure pathway).The probability density function is shown in Figure J.22.

Since the attenuation of gamma radiation within a volume source is calculated separately,this parameter should account only for the thickness of shielding material external to the volumesource. The user should ensure that the thickness entered does not exceed the distance betweenthe source surface and the receptor.

FIGURE J.22 Shielding Thickness Probability Density Function

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0 5 10 15 20 25 30 35 40

Shielding Thickness (cm)

f(x)

Triangular DistributionMinimum = 0 cmMaximum = 30 cmMost Likely = 0 cm

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J.5.2 Shielding Density

Definition: This parameter represents the effective bulk density of shielding between a receptorand a radiation source.

Parameter Name: DSDEN Units: g/cm3 Range: 0 to 22.5


Probabilistic Analysis Default Distribution (allowed only for concrete): uniformDefining Values for Distribution:Minimum: 2.2 Maximum: 2.6


Discussion: The type of shielding material, along with the shielding thickness and density,determines the gamma attenuation properties of the shield. This parameter is important for theexternal exposure pathway. For situations in which only air is between the source and receptor,the shielding thickness should be set to 0 and the density becomes immaterial. The type ofshielding material will often determine the density.

In the RESRAD-BUILD code, the user must input the shielding characteristics for eachsource-receptor pair (e.g., if there are 4 sources and 6 receptors, the code would require24 shielding characteristics). RESRAD-BUILD accommodates eight types of shielding materials:concrete, water, aluminum, iron, lead, copper, tungsten, and uranium. Table J.23 gives thedensity range (if appropriate) and a single value of density for the RESRAD-BUILD shieldingmaterials that have a narrow range (except concrete). The table lists ranges for cast iron and givesa single-value density for other materials. The values are taken from The Health Physics andRadiological Health Handbook (Shleien 1992) and from the CRC Handbook of Chemistry andPhysics (Lide 1998). Table J.24 provides the concrete density from three different sources: TheHealth Physics and Radiological Health Handbook (Shleien 1992), Properties of Concrete(Neville 1996), and Standard Handbook for Civil Engineers (Merritt et al. 1995). The value usedin the code is for ordinary concrete. If the type of concrete is known, a uniform distributionbetween the given range for a known concrete type can be used. The probability density functionfor concrete shielding density is displayed in Figure J.23.

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TABLE J.23 Density of Shielding Materials(except concrete) Allowed in RESRAD-BUILD

MaterialDensity

Range (g/cm3)Normal

Density (g/cm3)

Aluminum -a 2.7 Copper - 8.96 Lead - 11.35 Steel - 7.8 Cast iron 7.0�7.4Water - 1.0 Tungsten - 19.3 Uranium - 19.1 Iron - 7.87

a A dash indicates that data were not available.

Sources: Shleien (1992); Lide (1998).

TABLE J.24 Shielding (Concrete) Density from Various Sources

Concrete Density (g/cm3)

AggregateShleien(1992)

Neville(1996)

Merritt et al.(1995)

Ordinary (silicacious) or normal weight 2.2–2.4 2.2–2.6 2.3Heavy weight -a - 2.4–6.15Limonite (goethite, hyd. Fe2O3) 2.6–3.7 - -Ilmenite (nat. FeTiO3) 2.9–3.9 - -Magnetite (nat. Fe3O4) 2.9–4.0 - -Limonite and magnetite - - 3.35–3.59Iron (shot, punchings, etc.) or steel 4.0–6.0 - 4.0–4.61Barite 3.0–3.8 - 3.72Lightweight - 0.3–1.85 0.55–1.85Pumice - 0.8–1.8 1.45–1.6Scoria - 1.0–1.85 1.45–1.75Expanded clay and shale - 1.4–1.8 -Vermiculite - 0.3–0.8 0.55–1.2Perlite - 0.4–1.0 0.8–1.3Clinker - 1.1–1.4 -Cinders without sand - - 1.36Cinders with sand - - 1.75–1.85Shale or clay - - 1.45–1.75Cellular - 0.36–1.5. -No-fines - 1.6–2.0 1.68–1.8No-fines with lightweight aggregate - 0.64–higher -Nailing - 0.65–1.6 -Foam - - 0.3–1.75

a A dash indicates that data were not available.

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FIGURE J.23 Concrete Shielding Density Probability Density Function

0

0.5

1

1.5

2

2.5

3

2 2.2 2.4 2.6 2.8 3

Shielding Density (g/cm3)

f(x)


Minimum = 2.2 g/cm3

Maximum = 2.6 g/cm3

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J.5.3 Shielding Material

Definition: This parameter specifies the type of material used in the shield between the receptorand source.

Parameter Name: MTLC Units: Unitless

Range: Concrete, water, aluminum, iron, copper, tungsten, lead, or uranium

Default Value: Concrete


Discussion: This parameter is not eligible for probabilistic input. If air is the only mediumbetween the source and receptor, there is no shielding material present. The type of shieldingmaterial, along with the shielding thickness and density, determines the gamma attenuationproperties of the shield. This parameter is important only for the external pathway.

The user can select among eight shielding materials: concrete, water, aluminum, iron,copper, tungsten, lead, and uranium. This parameter can be determined from direct inspection,standard building codes, and/or building design specifications. When there are many materials inthe shielding, the input material that most closely approaches the weighted average atomicnumber of the shield should be chosen.

The code requires the shielding material parameter to be set for every source and receptorpair. For example, if there are two sources and four receptors, the code requires eightindependent shielding materials to be entered. It is up to the user to specify the correct densitiesfor the shielding materials (see Section J.5.2, Shielding Density).

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J.5.4 References

Ayers, K.W., et al., 1999, Reuse of Concrete from Contaminated Structures, prepared byDepartment of Civil and Environmental Engineering, Vanderbilt University, Nashville, Tenn.,for U.S. Department of Energy, Office of Science and Technology, Washington, D.C.

Lide, D.R. (editor-in-chief), 1998, CRC Handbook of Chemistry and Physics, 79th ed., CRCPress, Boca Raton, Fla.

Merritt, F.S., et al. (editors), 1995, Section 5, “Construction Materials,” in Standard Handbookfor Civil Engineers, McGraw-Hill, New York, N.Y.

Neville, A.M., 1996, Properties of Concrete, 4th Ed., John Wiley & Sons, Ltd., Brisbane,Australia.

Shleien, B. (editor), 1992, The Health Physics and Radiological Health Handbook, Rev. Ed.,Scinta, Inc., Silver Spring, Md.

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J.6 TRITIUM MODEL PARAMETERS

J.6.1 Dry Zone Thickness

Description: Dry zone thickness is the depth of the uncontaminated layer overlying the tritiumcontaminated (wet) layer.

Parameter Name: DRYTHICK Units: cm Range: 0–wet + dry zone thickness

Default Value: 0

Window: Source Parameters → Details

Discussion: The tritium vaporization model in RESRAD-BUILD considers only a volume sourcethat is situated inside the concrete wall or floor of a contaminated building. The user can specifythe depth of the dry zone, which is an uncontaminated region, and the depth of the wet + dryzone. The difference between these two depths gives the thickness of the contaminated zone.

The tritium vaporization model implemented in the RESRAD-BUILD code was adaptedfrom the landfarming model developed by Thibodeaux and Hwang (1982) to considervolatilization of hydrocarbons from contaminated soils. The model assumes that the vaporizationrate is controlled by the diffusion rate of water molecules through the pore space of the solidmaterial. The difference between the vapor concentration of water in the air and the vaporconcentration of water in the pore space of the contaminated zone is the driving force of thediffusion process. The vaporization of water is assumed to be similar to a peeling process inwhich, as time goes on, the free water molecules (those that do not adsorb to the solid matrix) inthe contaminated zone are peeled off layer by layer. This process creates a dry zone withincreasing thickness between the surface of the contaminated material and the remainingcontaminated zone inside the material. As water molecules vaporize, tritium is released to theindoor air and results in potential radiation exposure. To estimate the release rate of tritium, thevalues of several additional parameters (see Sections J.6.2 through J.6.5) are required. The codethen uses the values of these parameters to estimate the average tritium release rate over theexposure duration and the integrated radiation dose resulting from exposure.

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J.6.2 Wet + Dry Zone Thickness

Description: This parameter represents the depth from the surface of the contaminated materialto the deepest point of the contaminated zone.

Parameter Name: H3THICK Units: cm Range: ≥ 0


Probabilistic Analysis Default Distribution: Uniform(allowed only for volume contamination with tritium)Defining Values for Distribution:Minimum: 5 Maximum: 30


Discussion: The wet + dry zone thickness parameter is used in RESRAD-BUILD in modelingthe emission rate of tritiated water (HTO) vapor from the contamination source to the indooratmosphere. In a tritium-handling facility, tritium contamination of the construction material andthe equipment is recognized as an important source in defining the requirements for atmosphericcleanup and personnel protection. Tritium released during the handling process can quickly sorbto surfaces of the surrounding materials (e.g., concrete walls and floors) and can diffuse throughmany of them, resulting in contamination of the bulk as well as of the surface. The tritium that isabsorbed/adsorbed to the surrounding materials can then be desorbed and released to the indoorair. This sorption/desorption process is generally referred to as the “tritium soaking effect” intritium-handling facilities.

Tritium released from the tritium-handling facilities can be in different chemical forms;the most common ones are tritium gas (HT) and tritium oxide, or HTO. In general, sorption anddesorption of HT occurs faster than that of HTO; however, the total amount sorbed and desorbedis greater for HTO than for HT (Wong et al. 1991; Dickson and Miller 1992). In contrast, HT caneasily be converted to HTO in the environment. Experimental data concerning the tritiumsoaking effect on construction metals also showed that about 90% of the tritium desorbed frommetal samples was in the form of HTO, although the samples were exposed to an atmosphere ofHT (Dickson and Miller 1992). Because of the conversion from HT to HTO and the potentiallylonger time required for degassing of HTO (desorption and subsequent release from thecontaminated material to the indoor air), the tritium model incorporated into the RESRAD-BUILD code considers only the potential degassing of HTO after the tritium-handling operationhas stopped.

Among all the materials that can become contaminated, concrete is of special concernbecause of its high porosity. The high porosity of concrete materials makes them more vulnerable

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to the permeation of tritiated water, which can spread inside the concrete matrix after the initialsurface absorption/adsorption. In RESRAD-BUILD, the degassing (i.e., the release) of the HTOvapor is assumed to be controlled by diffusion of the free HTO molecules from inside of theconcrete matrix to the concrete-atmosphere interface (the “free” molecules are the HTOmolecules that are not bound to the concrete matrix and are available for diffusion, see discussionfor the “water fraction available for evaporation” parameter, Section J.6.4).

The diffusion of HTO is assumed to proceed like a peeling process in which the HTOmolecules closer to the concrete-atmosphere interface will be released earlier than those fartherfrom the interface. As the release process continues, a region free of free HTO molecules(i.e., the dry zone), will be formed, and its thickness will increase over time. The dry zonethickness then represents the path length for the subsequent diffusion. The region inside theconcrete where the free HTO molecules are distributed is called the wet zone. As the dry zonebecomes thicker, the thickness of the wet zone decreases accordingly. In fact, the sum of the dryzone thickness and the wet zone thickness is assumed to remain the same throughout thediffusion process.

Although diffusion of the HTO vapor to the bulk of concrete materials in a tritiumhandling facility is recognized (Wong et al. 1991), direct detection of the extent of spreading intothe bulk (i.e., dry + wet zone thickness) is not possible because of the short range of the betaradiation (DOE 1991). However, judging by the high porosity of concrete materials, spreading ofthe HTO vapor throughout the entire thickness is possible if the exposure is of sufficientduration. Therefore, the thickness of the concrete wall is assumed for the “dry + wet zonethickness” parameter, which, on the basis of engineering judgments, can be as much as 30 cm. Alow bound of 5 cm is selected because bulk contamination will not be extensive for a shortexposure period. The probability density function is shown in Figure J.24.

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FIGURE J.24 Wet + Dry Zone Thickness Probability Density Function

0

0.01

0.02

0.03

0.04

0.05

0.06

0 5 10 15 20 25 30 35 40 45

Wet + Dry Zone Thickness (cm)

f(x)

Uniform DistributionMinimum = 5 cmMaximum = 30 cm

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J.6.3 Volumetric Water Content

Description: The volumetric water content is the volume of water per unit volume of the porousmaterial.

Parameter Name: H3VOLFRACT Units: Unitless Range: >0 to 1


Probabilistic Analysis Default Distribution: Uniform(allowed only for concrete for volume contamination with tritium)Defining Values for Distribution:Minimum: 0.04 Maximum: 0.25


Discussion: The volumetric water content is used in RESRAD-BUILD when evaluating theradiological risks from a volume source contaminated with tritium. The assumption is made thatany tritium is present as tritiated water. Because the contamination medium is assumed to beconcrete, the amount of water in the volume source is expected to be within the range of theconcrete’s total porosity. Thus, the distribution for the volumetric water content is expected to bethe same as the source porosity (Section J.4.18). In any case, the maximum value assigned to thevolumetric water content should not be greater than the maximum of the source porosity.

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J.6.4 Water Fraction Available for Vaporization

Description: This parameter is used in estimating the potential release rate of tritiated water(HTO) vapor from a volume contamination source. It is the fraction of the total amount oftritiated water that will be released to the indoor air through the diffusion mechanism under roomtemperature.

Parameter Name: H3RMVF Units: Unitless Range: 0 to 1


Probabilistic Analysis Default Distribution: Triangular(allowed only for volume contamination with tritium)Defining Values for Distribution:Minimum: 0.5 Maximum: 1.0 Most likely: 0.75


Discussion: In a tritium-handling facility, tritium contamination of the construction material andthe equipment is recognized as an important radiation source in defining the requirements foratmospheric cleanup and personnel protection. Tritium released during the handling process canquickly sorb to surfaces of the surrounding materials and can diffuse through many of them,resulting in both bulk (volumetric) and surface contamination. The tritium that is absorbed oradsorbed to the surrounding materials can then be desorbed from the materials and released to theindoor air. This sorption/desorption process is generally referred to as the “tritium soaking effect”in tritium-handling facilities.

Tritium released from the tritium-handling facilities can be in different chemical forms;the most common ones are tritium gas (HT) and tritium oxide, or tritiated water (HTO). Ingeneral, sorption and desorption of HT occurs faster than that of HTO; however, the total amountsorbed and desorbed is greater for HTO than for HT (Wong et al. 1991; Dickson and Miller1992). On the other hand, HT can easily be converted to HTO in the environment. Experimentaldata concerning the tritium soaking effect on construction metals also showed that about 90% ofthe tritium desorbed from the metal samples was in the form of HTO, although the samples wereexposed to atmosphere of HT (Dickson and Miller 1992). Because of the conversion from HT toHTO and the potentially longer time required for degassing of HTO (desorption and subsequentrelease from the contaminated material to the indoor air), the tritium model incorporated into theRESRAD-BUILD code considers only the potential degassing of HTO after the tritium-handlingoperation has stopped.

Among all the materials that can become contaminated, concrete is of special concernbecause of its high porosity. The high porosity of concrete materials makes them more vulnerable

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to the permeation of tritiated water, which can spread inside the concrete matrix after the initialsurface absorption/adsorption. In RESRAD-BUILD, the degassing (i.e., the release) of the HTOvapor is assumed to be controlled by diffusion of the HTO molecules from inside of the concretematrix to the concrete-atmosphere interface.

The diffusion rate is estimated on the basis of the extent of the contamination (thicknessof dry zone, thickness of dry zone + wet zone, and area of contamination), characteristics of thesource material (porosity and moisture content), tritium inventory (tritium concentration), andindoor humidity. Because not all the tritium in the source material is available for diffusion underordinary building occupancy conditions, estimation of the release rate has to take into account thefraction of tritiated water available for vaporization and diffusion.

According to the experimental observations of Numata and Amano (1988), water existsin concrete in two states: free water and bound water. Free water is the liquid water that fills thepore space and capillaries in the concrete. Bound water is the water that combines withconstituent compounds in concrete or the concrete itself. The fraction of free water wasdetermined by Numata and Amano (1988) in their thermal desorption experiments as the fractionthat was desorbed from concrete samples when the heating temperature was less than 200ºC. Theexistence of free water versus bound water was verified in an investigation by Ono et al. (1992),who studied sorption and desorption of tritiated water on paints. That study found that recoveryof tritium sorbed to various paint materials was not complete by gas sweeping under 30ºC.Residual tritium sorbed was recovered by heating up the samples up to 800ºC. Although thesamples used by Ono et al. (1992) were different from the concrete samples used by Numata andAmano (1988), it is quite conclusive that some tritiated water can strongly bond with the sourcematerials. In the RESRAD-BUILD tritium model, it is assumed that under ordinary buildingoccupancy conditions, only the water that fills the pore space and capillaries of the concretematerials will vaporize and diffuse to the indoor atmosphere.

Numata and Amano (1988) reported that the fraction of free tritiated water in concretesamples depended on the duration of the previous exposure of the samples to tritiated watervapor. A shorter exposure duration resulted in a larger fraction of free tritiated water. However,as the exposure duration was increased to more than 60 days, equilibrium values were observed.The fraction of free tritiated water at equilibrium was 0.72 for hardened cement paste and 0.74for mortar. The fraction of free ordinary water was lower than that for tritiated water because theordinary water originally exists in the samples and was the residual water left duringcrystallization of the cement samples. The free fraction was about 0.58 for both hardened cementpaste and mortar samples. The free fractions of ordinary water reported by Numata and Amano(1988) are consistent with the suggestion in DOE (1994) regarding the air release fraction oftritiated water from concrete materials under accidental conditions that can cause the temperatureto reach as high as 200ºC. Tritiated water was assumed in the DOE report to be used in concreteformation, which is the same role as ordinary water in Numata and Amano’s experiments.

On the basis of the above discussion, the following conclusions can be made: (1) the freefraction of tritiated water in concrete materials used in tritium-handling facilities is greater than

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the free fraction of ordinary water in the same materials and (2) the free fraction of tritiated waterin the concrete materials can be very high if the exposure duration of the concrete materials totritiated water was very short. Therefore, a triangular distribution with a minimum of 0.5, amaximum of 1.0, and a most likely value of 0.75 was assumed for the “free water fractionavailable for evaporation” parameter. The probability density function is shown in Figure J.25.

FIGURE J.25 Water Fraction Available for Evaporation ProbabilityDensity Function

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Water Fraction Available for Evaporation

f(x)

Triangular DistributionMinimum = 0.5Maximum = 1.0Most Likely = 0.75

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J.6.5 Humidity

Description: This parameter represents the average absolute humidity in the building. Theabsolute humidity is an input used only for the tritium volume source model.

Parameter Name: HUMIDITY Units: g/m3 Range: 0 to 100


Probabilistic Analysis Default Distribution: Uniform(allowed only for volume contamination with tritium)Defining Values for Distribution:Minimum: 6.5 Maximum: 13.1


Discussion: RESRAD-BUILD requires input for the absolute humidity, the actual concentrationof water vapor in air. The relevant data available are given in terms of the relative humidity(RH). The RH of a water vapor-air mixture is defined as 100 times the partial pressure of waterdivided by the saturation vapor pressure of water at the same temperature. For this discussion,RH was converted to absolute humidity by assuming a total pressure of 1 atmosphere inconjunction with a given temperature and partial pressure of water at that temperature. Tabulatedvalues for the partial pressure of water over a range of temperatures were obtained from Dean(1999).

For RESRAD-BUILD, the average humidity in a building depends on the functioning ofthe heating, ventilation, and air-conditioning (HVAC) systems of the building. At normal roomtemperatures, the RH in occupied buildings should be between approximately 30 and 60% tohelp maintain human health and comfort (Sterling et al. 1985). With respect to health, this rangein RH minimizes allergic reactions and bacterial and viral growth. Human discomfort is noted atlower and higher humidities. Discomfort at low RH results from the drying of skin, hair, andrespiratory membranes.

Because HVAC systems are designed to maintain a healthy environment for buildingoccupants (the 30 to 60% RH range), a uniform distribution for the corresponding absolutehumidity range is used as the default distribution in RESRAD-BUILD. The range of 30 to 60%RH corresponds to an absolute humidity range of 6.5 to 13.1 grams of water per cubic meter at1 atmospheric pressure and 24ºC (75ºF). The probability density function is shown inFigure J.26. However, RH values lower than 30% may occur in buildings that do not have ahumidification system, especially during the winter in colder climates. Also, RH values higherthan 60% may occur in buildings using natural ventilation in more temperate climates. In such

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climates where natural ventilation may be employed, the humidity inside the building will bemore representative of the outside levels.

For those buildings more dependent on natural ventilation, data from 231 weather stationsacross the conterminous 48 United States, most with more than 30 years of recorded data, wereanalyzed to obtain a perspective on ambient outdoor humidity levels. Annual average morningand afternoon RH levels were used in conjunction with annual average temperature readings atthese weather stations (National Climatic Data Center [NCDC] 1999) to estimate absolutehumidity levels. The morning and afternoon RH levels were averaged for each station to obtainone value for the annual average RH for use in estimating the absolute humidity.

The resulting absolute humidity probability density function was fit reasonably well to alognormal distribution by using Bayesian estimation, as shown in Figure J.27. This distribution isonly indicative of what might be expected. The sampling is not representative of a uniform gridacross the United States, although it is indicative of the larger population centers. Whenavailable, site-specific data should be used. For this alternative distribution, the underlying meanand standard deviation for the lognormal fit are 1.98 and 0.334, respectively.

FIGURE J.26 Default Indoor Absolute Humidity Probability Density Function

0

0.05

0.1

0.15

0.2

0.25

4 5 6 7 8 9 10 11 12 13 14 15

Absolute Humidity (g/m3)

f(x)


Minimum = 6.5 g/m3

Maximum = 13.1 g/m3

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FIGURE J.27 Representative Probability Density Function for OutdoorAmbient Humidity

0

5

10

15

20

25

30

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

Absolute Humidity (g/m3)

Fre

quen

cy

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

f(x)

Frequency

f(x)

Lognormal DistributionUnderlying � = 1.98Underlying � = 0.334

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J.6.6 References

Dean, J.A., 1999, Lange’s Handbook of Chemistry, 15th Ed., McGraw-Hill, Inc., New York,N.Y.

Dickson, R.S., and J.M. Miller, 1992, “Sorption of Tritium and Tritiated Water on ConstructionMaterials,” Fusion Technology 21:850–855.

DOE: See U.S. Department of Energy.

National Climatic Data Center, 1999, Comparative Climatic Data for the United States through1998, National Oceanic and Atmospheric Administration, U.S. Department of Commerce,Washington, D.C.

Numata, S., and H. Amano, 1988, “Tritium Permeation into Concrete,” pp. 1260–1264 in FusionTechnology, Proceedings of the 15th Symposium on Fusion Technology, Utrecht, Netherlands.

Ono, F., et al., 1992, “Sorption and Desorption of Tritiated Water on Paints,” Fusion Technology21:827–832.

Sterling, E.M., et al., 1985, “Criteria for Human Exposure to Humidity in Occupied Buildings,”ASHRAE Transactions 91(1B):611–622 as cited in ASHRAE, 1996, Heating, Ventilating, andAir-Conditioning Systems and Equipment Handbook, SI Ed., American Society of Heating,Refrigerating, and Air-Conditioning Engineers, Inc., Atlanta, Ga.

Thibodeaux, L.J., and S.T. Hwang, 1982, “Landfarming of Petroleum Wastes — Modeling theAir Emission Problem,” Environmental Progress 1(1):42.

U.S. Department of Energy, 1991, Recommended Tritium Surface Contamination ReleaseGuides, Tritium Surface Contamination Limits Committee, U.S. Department of Energy,Washington, D.C., Feb.

U.S. Department of Energy, 1994, DOE Handbook, Airborne Release Fractions/Rates andRespirable Fractions for Nonreactor Nuclear Facilities, Volume 1 — Analysis of ExperimentalData, DOE-HDBK-3010-94, U.S. Department of Energy, Washington, D.C., Dec.

Wong, K.Y., et al., 1991, “Tritium Decontamination of Machine Components and Walls,”Fusion Engineering and Design 16(1991):159–172.

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J.7 RADIOLOGICAL UNITS

J.7.1 Activity Units

Definition: Any of the following four units of radiological activity can be selected: (1) Ci orcurie, defined as 3.7 × 1010 disintegrations per second (dps); (2) Bq or becquerel, defined as1 dps; (3) dps; (4) disintegrations per minute (dpm). Any standard one-character metric prefixcan be used with Ci and Bq. The allowed prefixes are as follows:

E exa 1 × 1018

P peta 1 × 1015

T tera 1 × 1012

G giga 1 × 109

M mega 1 × 106

k kilo 1 × 103

h hecto 1 × 102

none 1d deci 1 × 10-1

c centi 1 × 10-2

m milli 1 × 10-3

m micro 1 × 10-6

n nano 1 × 10-9

p pico 1 × 10-12

f femto 1 × 10-15

a atto 1 × 10-18

Default: pCi (picocurie)

Window: Radiological Units

Discussion: The choices for activity include Ci, Bq, dpm, and dps. Both the Ci and Bq settingsallow the user to specify a prefix that ranges over 36 orders of magnitude. The activityconcentration values in each source are automatically converted to reflect the activity unitchange.

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J.7.2 Dose Units

Definition: The dose equivalent or equivalent dose is the average absorbed dose over a tissue ororgan and weighted for the radiation quality that is of interest. The effective dose equivalent oreffective dose is the sum of the weighted equivalent doses in all tissues and organs of the body.Either of the two biological radiation dose units, rem or sievert, can be selected. The rem is theconventional unit of dose equivalent, effective dose equivalent, equivalent dose, and effectivedose; 1 rem = 0.01 Sv. The sievert (Sv) is the name for the SI unit of dose equivalent, effectivedose equivalent, equivalent dose, and effective dose; 1 Sv = 100 rem. Any standard one-charactermetric prefix can be used with rem or Sv. The allowed prefixes are as follows:

E exa 1 × 1018

P peta 1 × 1015

T tera 1 × 1012

G giga 1 × 109

M mega 1 × 106

k kilo 1 × 103

h hecto 1 × 102

none 1d deci 1 × 10-1

c centi 1 × 10-2

m milli 1 × 10-3

m micro 1 × 10-6

n nano 1 × 10-9

p pico 1 × 10-12

f femto 1 × 10-15

a atto 1 × 10-18

Default: mrem (millirem)

Window: Radiological Units

Discussion: The choices for dose include rem and Sv. Both have the prefix option. The doseunits are used only for reporting results.

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Documents

User’s Manual for RESRAD-BUILD Version 3 · ANL/EAD/03-1 User’s Manual for RESRAD-BUILD Version 3 Environmental Assessment Division Argonne National Laboratory Operated by The